JP2001519192A - Scanning Target Detection for Computer Tomography - Google Patents

Abstract

Using a helical cone beam (114) scanning, a swiveling slice CT system generates three-dimensional projection data and an equal tilt with respect to the longitudinal axis of the scanned object. Reconstruct a series of flat image slices (132) having angles (θ) and varying angles of rotation, causing their normals to oscillate, and with respect to the longitudinal axis (Z) To process. Conventional two-dimensional reconstruction is used. This is because the projection data (130) of the tilted slice (132) is one-dimensional fan beam data. A two-dimensional image can be generated at a stationary projection angle. Voxel swing or tilt can be corrected, and parallel processing can be used.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

TECHNICAL FIELD OF THE INVENTION

The present invention generally relates to computer tomography (CT) image processing.
In particular, it relates to CT image processing with improved efficiency and reduced image artifacts.

[0002]

BACKGROUND OF THE INVENTION

FIG. 1 is an axial schematic diagram of a typical conventional CT scanner 10 that includes an X-ray source 12 and an X-ray detector system 14 that is fixed on opposite sides of an annular disk 16. is there. The disk 16 is rotatably mounted inside a gantry (not shown) so that during scanning, the disk 16 rotates continuously around the z-axis, while X-rays are emitted inside the opening of the disk 16. X-rays pass from the source 12 through an object such as the patient 20 placed on a patient table 56 at The z-axis is perpendicular to the plane of the page in FIG. 1 and intersects the scan plane at the mechanical center 18 of rotation of the disk 16. The mechanical center 18 of the rotation of the disk is
It corresponds to the "isocenter" of the reconstructed image.

In one conventional system, the detector system 14 includes a point 24 called a “focal spot” where radiation is emitted from a source 12 of X-rays.
Individual detectors 22 arranged in a single row in the form of an arc with a center of curvature
Arrays. The array of sources 12 and detectors 22 are arranged such that the x-ray paths between the sources and each detector are all in a "scan plane" perpendicular to the z-axis. The x-ray path is incident on the detector array 14 in the form of a one-dimensional linear projection, since the x-ray path extends at different angles to the detector from a location that is substantially one point source. Forming a “fan beam” 26. X-rays that are incident on a single detector at one measurement instant during a scan are commonly referred to as "rays" and each detector produces an output signal indicative of the intensity of its corresponding light beam. . Since each ray is partially attenuated by all the masses in its path, the output signal generated by each detector will be equal to all the signals located between that detector and the source of the X-rays. It represents the attenuation of the mass, ie the attenuation of the mass lying in the path of the corresponding light beam of the detector.

[0004] The output signal generated by the X-ray detector is usually processed by a signal processing portion (not shown) of the CT system. The signal portion generally includes a data acquisition system (DAS), which filters the output signal generated by the X-ray detector to improve its signal-to-noise ratio (SNR). D during the measurement interval
The output signal generated by the AS is commonly referred to as a "projection" or "view", and the angular orientation of the disk 16, source 12, and detector system 14 corresponding to one particular projection is " It is called the "projection angle."

FIG. 2 shows the orientation of the disk 16, X-ray source 12 and detector system 14 for the generation of the fan beam data point P _f (β, γ) at the projection angle β and the detector angle γ. Is shown. A centerline 40 used to define the orientation of the reference extends from the focal point of the source of x-rays 12 at the mechanical center 18 of rotation through the z-axis. The projection angle β is defined as the angle between the vertical axis and the center line 40. Associated with each individual detector in system 14 is a detector angle γ, also defined with respect to centerline 40. By definition, centerline 40 intersects detector system 14 at a reference detector angle γ of 0 °. A symmetric detector system 14 as shown in FIG. 2 extends from a detector angle of -δ to + δ,
Here, δ is half the angle of the fan. The view or projection P _f (β, γ) of the fan beam generated by the symmetric detector system 14 is generated by all detectors at detector angles from −δ to + δ with _{respect to} the projection angle β. Includes a set of data points P _f (β, γ). Asymmetric detector systems are also well known.

[0006] During scanning, the disc 16 smoothly and continuously moves around the object to be scanned.
And the scanner 10 rotates one set of projections P in the corresponding set of projection angles β. _f (Β, γ) can be generated. In a conventional scan, the patient remains at a constant z-axis position during the scan. When taking multiple scans, the patient may
Is moved stepwise along the z-axis. These processes are usually "step
Called "and-shoot" scanning or "constant z-axis" (CZA) scanning.
Using well-known algorithms such as the inverse Radon transform,
Tomograms can be generated from a set of projections that all share the same scan plane.
Wear. This common scan plane is commonly referred to as a "slice plane."

A tomogram represents the density of a two-dimensional slice along the slice plane of the object being scanned. The process of generating a tomogram from a projection is commonly referred to as "reconstruction." This is because the tomogram is considered to be reconstructed from the projection data. The reconstruction process is a convolution to remove data blur, parallel beam data from fan beam beam data, and back-projection where the image data for each image pixel is generated from its projection data. Several steps may be included, including rebinning. In a CZA scan for a particular image slice, all projections share a common scan plane, and therefore these projections can be applied directly to a back projector for tomogram generation.

[0008] The method of step-and-shoot CZA scanning can be a slow process. In this time consuming method, the patient may be exposed to large amounts of X-ray radiation. Also, as the scan table is moved between each scan, patient motion can result in motion and misregistration artifacts that can result in degraded image quality.

Several methods have been developed to reduce the time required to obtain a full scan of an object. One of these methods is a helical or helical scan, in which the object being scanned is in the z-axis while the source 12 and the linear detector array 14 are rotated around the patient. Moved along. In a helical scan, the projections P _f (β, γ) are usually collected such that z is linearly related to the view angle β such that z (β) = cβ. Here, c is a constant. This type of helical scan is commonly referred to as a constant speed helical (CSH) scan.

FIG. 3A shows data collected during a conventional CZA scan, and FIG.
Figure 3 shows data collected during an SH scan. As shown in FIG. 3A,
X-ray source 12 and detector system 1 while the object remains at a fixed z-axis
4 are rotated about the object 20, the scan planes associated with all projections collected by the detector system 14 will all be in a common slice plane 50. As shown in FIG. 3B, if the object 20 is continuously moved in the direction of the z-axis while the disk is rotating around the object 20, any scan plane will be in the same plane. There is no. Conversely, the scan plane associated with each projection is at a unique position along the z-axis at one locus point on the set of trajectory spirals. FIG. 3B shows the scan plane z corresponding to the helix projection angle in the interval (0,10π).
The axis coordinates are shown. Since the value of each projection depends on the patient's z-axis position, each projection can be considered to be a function of two variables, β and z.

In CZA scanning, all projections share a common scan plane, so these projections can be applied directly to the back projector to generate a tomogram. However, in CSH scanning, each projection has a unique scan plane at a unique z-axis coordinate, and therefore the CSH projection cannot be applied directly to the back projector. But,
The data collected during the CSH can be interpreted in various ways to generate a set of interpreted projections that all share one common scan plane that extends perpendicular to the z-axis. . Each interpreted projection can be generated, for example, by combining two projections taken at equivalent projection angles and at different z-axis locations. These interpreted projections can be treated as CZA data and applied to a back projector to generate a tomogram.

[0012] Scanning CSH requires some form of interpretation to generate a tomogram, and thus the tomogram generated by scanning CSH tends to be characterized by image artifacts. Also, the CSH scan projection data is collected over one interval at the z-axis location and combined to produce interpreted CZA scan data, so that the effective tomogram generated during CSH scanning is obtained. The width of the slice plane is wider, and thus the resolution of the z-axis is lower than the tomogram generated by CZA scanning. However, helical scanning is advantageous because it allows rapid scanning of large volumes of the patient. For example, a helical scan scans an entire organ, such as the kidney, in a time interval that is short enough that the patient can comfortably hold his breath (and thereby remain relatively immobile). Enough data to be collected.

Another method for reducing scan time compared to CZA scanning is commonly referred to as “cone beam scanning”. In that method, a three-dimensional volume of the object or patient is scanned at a time. In cone beam scanning, the detection system includes a two-dimensional array of detectors instead of the one-dimensional array used in conventional scanning. The x-ray output from the source diverges in two dimensions to produce multiple equivalent fan beams along the z-axis. It illuminates the rows of the detectors, thus forming a two-dimensional projection on the detectors.

In one type of cone beam system, the patient or object is at a stationary z-axis position while the source and the two-dimensional detector array are rotated around the patient or object. Will be maintained. Next, the patient is moved to the new z-axis position and the scan is repeated. In this type of step-and-shoot or "stationary cone beam" system, rather than sweeping one plane, the volume of the object is scanned. After one volume has been scanned, the source and detector are moved stepwise along the z-axis to scan the next volume. Yet another method used to reduce scan time is helical cone beam (HCB) scanning, in which a patient is moved around the patient while being continuously moved in the z-axis. The cone beam configuration, ie, the source and the two-dimensional detector array are rotated.

[0015] Standard two-dimensional reconstruction techniques, such as two-dimensional filter-back projection (FBP), are used to reconstruct CZA and interpreted CSH data in non-cone beam systems. FBP requires that the set of projections used for reconstruction be in the same plane. This condition is satisfied in CZA scanning and C
Interpretation is used in SH scanning to generate a set of interpreted or simulated linear projections that effectively satisfy this condition. In either case, two-dimensional FBP is an efficient means of generating image data from one-dimensional fan beam projection data.

In the cone beam geometry, the necessary condition is satisfied only for the detector row in the same plane as the source in the plane perpendicular to the z-axis, ie the central detector row. Is done. In a stationary cone beam CT, as the gantry rotates, a one-dimensional projection defined by a source and a given detector traverses different slices in the object. By treating each row as an independent one-dimensional projection using a conventional two-dimensional FBP, the cone beam data can be reconstructed. This approximation ignores the geometry of the cone beam, produces image artifacts such as fringes, and results in a reduced reconstructed density. corn·
A better approximation method used to reconstruct the beam data is known as the Feldkamp algorithm and is described in L.W. A. Feldkamp et al. "Practical cone-bea"
M. algorithm, a practical cone beam algorithm. Op
t. Soc. Am. 1, pp. 612-619 (1984).

In the Feldkamp algorithm, rays are backprojected in a three-dimensional cone. Algorithms such as Feldkamp, which attempt to incorporate true cone beam geometry data, use three-dimensional filter-back projection (3D-FBP).
) Called the algorithm. Three-dimensional algorithms for reconstructing HCB data have also been developed. Examples of these algorithms are described in the following paper.

[0018] 1. H. Kudo and T.W. Saito, "3D Helical Scanning Computer Tomography Using Cone Beam Projection" J
own of Electronics, Information, an
d Communication Society J74-D-II, 110
8-114, (1991).

[0019] 2. D. X. Yan and R.M. Lee, "Cone-
beam Tomography with circular, ellipt
icals and spiral orbits "(cone beam tomograms with circular, elliptical and spiral trajectories) Phys. Med. Biol. 37
493-506, (1992).

[0020] 3. S. Schaller, T.W. Flohr and P.M. Stephan (Steffen), "New efficient Fo
urier reconstruction method for appr
oximate image reconstruction in spir
al cone-beam, CT at small cone angles
(New efficient Fourier reconstruction method for rough image reconstruction in CT of helical cone beams at small cone angles), SPIE Internet
ionical Symposium on Medical Imaging, 1
(February 997)

[0021] 4. G. FIG. Wang, TH Phosphorus (Lin), P.E. Chen (Ch
eng) and D.E. M. Shinozaki, "a general cone bea
algorithm (general cone beam algorithm), IEEE
E Trans. Med. Imag. 12, 486-496 (1993). One drawback of three-dimensional reconstruction algorithms is that they cannot be used with common two-dimensional reconstruction hardware, and consequently require custom three-dimensional back projection hardware to handle them. It is something that must be made.

In many CT scanning applications, it is desirable to pre-screen (screen) the region before performing the reconstruction. For example, certain suspicious objects, such as tumors, may be identified by a pre-screening process during CT imaging of sulfur for later closer inspection. CT scanning can also be applied to the identification of prohibited items, such as weapons and explosives, in baggage that are carried or loaded on commercial aircraft. It is often desirable to pre-screen bags to identify suspected bags. It can then be the symmetry of reconstruction of a complete CT image if the prescreening process identifies a suspicious target. In one conventional method for pre-screening, a separate line scanner generates a two-dimensional projection through the object being scanned, for example, a patient's luggage, to identify suspicious areas. Used for If a suspicious target is identified, the object can then be subjected to a full CT scanning and reconstruction. This process can be time consuming, and in baggage scanning applications, may not be practical given the rate at which luggage must be screened at commercial airports.

[0023]

[Object of the invention]

One object of the present invention is to substantially overcome the above identified disadvantages of the prior art.

Another object of the present invention is to provide a CT system with reduced image artifacts.

Yet another object of the present invention is to provide a CT system that provides image quality of a three-dimensional reconstruction algorithm using two-dimensional reconstruction hardware.

Still another object of the present invention is to achieve the above object in a helical cone beam scanning CT system.

Yet another object of the present invention is to efficiently generate a two-dimensional projected image of an object from CT scan data, which can be applied to situations such as baggage scanning where high scan throughput is required. Is to provide appropriate means.

Yet another object of the present invention is to provide detection of a target, such as by summing the mass associated with a volume element of a CT image, where the volume element is a CT scanning element. It is inclined with respect to the longitudinal axis of the scanning area of the system.

[0029]

Summary of the Invention

Accordingly, the present invention is directed to a CT apparatus and method for generating image data for a region. The area defines a longitudinal axis and an orthogonal transverse axis. An array of radiation sources and detectors is used to scan the area, and scanned data representing the area is generated. In one embodiment, a method of helical cone beam scanning is used to scan the area. At each of a plurality of positions along the longitudinal direction, or equivalently, at each of a plurality of projection angles, a slice of the two-dimensional image data is defined. Each data slice defines one slice plane that is inclined with respect to the longitudinal axis of the region. That is, the normal axis of each slice plane is inclined at a certain inclination angle with respect to the longitudinal axis of the area. The normal axis also defines the angle of rotation about the horizontal axis of the region. Successive slices along the longitudinal axis define a normal axis that defines an equal angle of inclination with the longitudinal axis of the region. Also, the rotation angle for successive slices increases along the longitudinal axis. The consequence of the increase in constant tilt and rotation angles is that the normal axis defines precession and oscillating movement about the longitudinal axis of the region through successive slices. In this geometry, the slices can be said to oscillate with respect to each other. At each image slice, an image of that region is generated where the image data has been calculated from the scan data. The reconstruction process for successive slices is referred to hereafter as the "swing slice reconstruction" (NSR) method.

The NSR method of the present invention is preferably used to reconstruct helical cone beam data using conventional two-dimensional filter-back projection. NSR
In, a set of one-dimensional fan beam projections is extracted from the two-dimensional cone beam projection data using interpolation. Therefore, the NSR needs to select two-dimensional fan beam data from three-dimensional cone beam data.
The set of one-dimensional projection data corresponds to a reconstructed slanted slice whose geometry has been chosen to minimize the undesirable effect of cone angle on image quality when using two-dimensional FBP. I do.

Traditionally, when reconstructing a series of slices, each slice is in the xy plane at a different location along the z-axis. That is, all slices in the series are parallel to each other. In NSR, the normal vector to the reconstructed slice plane is tilted by a small angle with respect to the z-axis. In a series of adjacent slices reconstructed in NSR, the normal vector to that slice plane is z
Precesses about an axis and the slices are not parallel to each other. The term "swinging" in the NSR refers to the relative orientation of adjacent slices. If parallel slices are needed, the resulting NSR image data can be interpreted to provide parallel slices.

In one embodiment, the X-ray source is a cone beam source,
And the array of detectors is a two-dimensional array. The scan data for each projection is determined from a predetermined one-dimensional line of detectors on the array. The detector used for a given projection or slice is associated with a position along the projection angle or longitudinal axis. At each position or projection angle, a group of detectors that minimizes errors in the measurement is selected. Thus, each slice is associated with a projection angle, a longitudinal position, and a group of detectors that define a one-dimensional "fan beam" projection on a two-dimensional detector array. When a particular slice is reconstructed, its scan data is generated from its associated detector in a two-dimensional array.

In another aspect, the present invention is directed to an apparatus and method for providing a two-dimensional projected image of a region from scan data generated for the region. Each slice of the head movement is generated from a set of fan beam views or projections that are reclassified into parallel ray projection data, each view or projection being obtained at a respective view angle. In the present invention, the projection angle for the two-dimensional projection image is selected as an angle at which the two-dimensional projection image is collected. For each slice, the view angle associated with the selected projection angle is identified, and the parallel ray projection data associated with the view angle is selected.
A two-dimensional projection image at the selected projection angle is generated by reclassifying the selected parallel ray projection data for the selected view angle for each slice in the scan data. In one embodiment, a plurality of two-dimensional projection images can be generated at a plurality of projection angles. These multiple projection images can be generated from a set of single scan data. The length of the projected image along the z-axis is equal to the axial extent of the slice used to form the projected image.

In one embodiment, the size of the object projected at the selected projection angle can be determined using a two-dimensional projected image. By identifying the boundaries of the object in the two-dimensional projected image, the size and location of the object within its field of view can be determined. The size and location of the object can then be used to identify areas of the field of view that do not need to be reconstructed. Because they do not provide information about the object. This "adaptive field of view" can be very useful in systems where scanning throughput is important, such as in bag scanning systems. This feature was filed on the same date as the present invention, is commonly assigned to non-assignees, and is hereby incorporated by reference. "Computed" by Gordon et al.
Tomography Scanning Apparatus and M
etc. Using Adaptive Reconstruction
A description and claim is made in a U.S. patent application entitled "Windows" (an apparatus and method for scanning computer tomography using an adaptive reconstruction window).

In another aspect, the present invention provides a method for detecting a target, such as an explosive, using a swing type image slice generated according to the method of the swing slice reconstruction of the present invention, and Is directed at the device. In this aspect of the invention, the tilt or swing of the slice is corrected to provide accurate target identification. Scanning data for the area where the object is located is obtained by scanning the area with an array of radiation sources and detectors. Using the scan data, a plurality of non-parallel image data slices are defined to correspond to a plurality of locations along the longitudinal axis of the region. Each slice defines a volume element, or "voxel," of the image that is inclined with respect to the longitudinal axis of the region, and each voxel is associated with an image density value derived from the scan data. To correct the tilt of the volume element of the image, one correction factor is applied to the image density value of the tilted volume element.

In one embodiment, the image density values are used to determine the mass of an object in the analysis of such an explosive. Determining the mass of an explosive will help assess the potential danger it will throw. The density value for each voxel associated with the object can be multiplied by the volume to determine the mass represented by the voxel. The calculated masses of all identified voxels associated with the target, ie, the explosive, are then summed to determine the total mass of the object. Correction for voxel tilt provides a more accurate determination of mass so that a better assessment of risk can be obtained.

As described above, the total mass of the object is determined by identifying the voxel associated with the object in question, ie, the explosive, correcting for the voxel slope, and determining the identified voxel. Can be calculated by summing the mass for Identifying the relevant voxels may be performed by applying a density value associated with each voxel to a density threshold. The threshold is selected based on the known density of the known substance, ie, the explosive. Values that exceed that threshold are concluded to be associated with the target substance, and thus their associated voxels are concluded to be associated with the target substance image. These voxels are used in calculating the total mass. In the present invention, they are applied to a correction factor used to correct the voxel tilt with respect to the longitudinal axis of the region. The products of the corrected volume and the associated density are then summed to determine the total mass. The density threshold determination can be realized by applying the volume element to a multiplication window function. Values above that threshold are applied to the unit multiplier in the window, and values that do not exceed the threshold are applied to the zero multiplier, effectively discarding them from the total mass calculation. .

In another aspect, the present invention provides a processing method and method for providing efficient processing of generated swiveling image data slices in accordance with the method of the present invention for slice reconstruction of a swiveling motion. Pointed to the system. This aspect of the present invention provides a plurality of independent processing paths for a group of image slice data, instead of a more conventional method of processing a pipeline in which slices are processed serially. Provide an architecture. According to this aspect of the invention, scan data for an area is generated by scanning that area with an array of radiation sources and detectors. To scan the region, at least the source of the radiation rotates about the longitudinal axis of the region through a plurality of viewing angles, and the source of radiation directs radiation toward an array of detectors .
Thus, the scan data includes a plurality of sets of projection data, each set of projection data being taken at a respective view angle. According to the method of the present invention for a slice reconstruction of a swing motion, each set of projection data includes a plurality of projections, for example, a fan beam projection. Each fan beam projection in the set of projection data produces a plurality of image data slices in each set of projection data that are used to generate a respective plurality of image data slices. Used to Further, each image data slice is generated from a plurality of fan beam projections, and a single fan beam projection is taken from each of the plurality of sets of projection data for that slice. Thus, in the present invention, slice data for each image data is generated from the respective set of associated fan beam projections. Each image data slice is associated with a respective data storage element (in one embodiment, a memory circuit). The projection from the image data slice to be generated is stored in a data storage element. The stored projections from each data storage element are processed to generate slice data for the image data slice associated with that data storage element.

In one embodiment, the processor receives the scan data from the array of detectors and generates a fan beam projection from the set of projection data within the scan data according to the NSR method described above. Next, the processor transfers the projection to the data storage element associated with the image data slice being played.
A demultiplexer circuit may be inserted between the processor and the data storage element to control the forwarding of the slice data projections to the respective associated data storage element.

In one embodiment, instead of a single processor generating the projections in a pipelined manner, multiple processors operating in parallel can be used. In this case, each image data slice to be generated is associated with a single processor that generates a projection for that slice. The projection is transferred by the associated processor to the associated data storage element, eg, a memory circuit, from which the projection is invoked to generate slice data for the image data slice. In one embodiment, one or more demultiplexer circuits can control the transfer of projections to the data storage element between the plurality of processors and the plurality of data storage elements. 1
In one embodiment, all of the processors can transfer projections to any data storage element. In other embodiments, each processor may transfer projections only to a selected group of data elements. By using multiple processors, processing the scan data into image data slices is performed much faster and more efficiently than with a single processor pipeline.

In one embodiment, the slice data is further processed to generate the actual image data slice, which is further used to generate an image of the region. This additional processing may include filtering and / or back projection to generate image slices. As noted above, the projection generated by the processor and / or processors is typically a fan beam projection. In one embodiment, the fan beam projections can be further processed to reclassify them into parallel beam projections. In one embodiment, multiple processors are used, one of which is used to perform the reclassification procedure, while the other processor continues to be used to generate the projection. Will be One processor may temporarily switch to the reclassification procedure, and then switch back to generating projections after the reclassification is complete. This saves considerable hardware by eliminating the need for additional dedicated processors for reclassification.

The CT apparatus and method of the present invention offers a number of advantages over conventional methods. It provides a method of three-dimensional scanning in the form of helical cone beam scanning, which consumes much less time than conventional methods using linear detector arrays. It provides a reconstruction process with image quality comparable to the three-dimensional reconstruction algorithm, but does not require three-dimensional reconstruction hardware. Much simpler two-dimensional reconstruction hardware is used. Further, the method of generating a two-dimensional projection image used in the present invention is a method of generating a projection image as part of a conventional baggage scanning system where a separate line scanner is used to generate the projection image as part of the prescanning process. It is much more efficient than traditional methods such as those used inside. By compensating for swinging motion or voxel tilt, the present invention can provide target detection and determination of target size and mass with improved accuracy compared to methods that do not correct voxel tilt. . Also, by applying the method of head slice reconstruction to the parallel processing architecture of the present invention, images can be generated much more efficiently than when the conventional pipeline method is used. .

[0043]

[Detailed description of drawings]

FIG. 4 is a schematic diagram illustrating the functional operation of one embodiment of the CT scanning system 100 of the present invention. The system includes a two-dimensional X-ray detector array 112.
And an X-ray source 110 for irradiating the X-ray with the X-ray. Detector array 112 is shown as a flat array with coordinates z 'and q. Curved arrays can also be used. The X-rays diverge into a cone beam passing through the object 116 being scanned. X-rays attenuated by object 116 are detected by individual detectors 118 in detector array 112. The detector array 112 includes a plurality of detector rows 120 along the z 'axis and a plurality of columns 124 along the q axis. Thus, the cone beam 114 can be considered to be composed of a plurality of fan beams that extend along the q-axis and are adjacent to each other along the z′-axis. Object 116 defines a z-axis (also referred to herein as a longitudinal axis) and an orthogonal x-axis (also referred to herein as a horizontal axis).

As described above, the x-ray source 110 and the detector array 112 are fixed on opposite sides of an annular disk (not shown). The disk is rotatably mounted inside a gantry (not shown), and the source 110 and detector array 112 can rotate simultaneously about the z-axis, and thus about the object 116 being scanned. .

In one embodiment, the system 100 uses helical cone beam scanning, and as the gantry rotates about the z-axis, the gantry and object 116 also move relative to each other along the z-axis. It is. As the gantry with the source and detector array moves along the z-axis, it rotates with increasing projection angle β. At each projection angle, scan data is collected by the detector array. Next, image data in the form of a series of image slices is reconstructed from the projection data. Each slice defines a flat configuration of image data, and is generated from a predetermined set of scan data collected as the source and detector arrays rotate.

In the present invention, a three-dimensional scanning method, that is, scanning of a helical cone beam is used, but image data can be generated using a two-dimensional reconstruction method. To accomplish this, the present invention projects a slice of two-dimensional data onto an array of two-dimensional detectors, such that the projection of the slice at each projection angle is considered to be a one-dimensional fan beam projection. To In the general case, the projections on the array fall on groups of detectors that are not necessarily in a single row or column. In fact, in general, the projection extends across several rows and columns. In the present invention, these rows and columns are identified for each projection angle. In one embodiment, interpreting the projection data generates a value from the projection data for each position at each projection angle. Thus, for each projection angle, a "fan beam" of detected data is generated, which is the fan beam generated in a two-dimensional fan beam scanning application using a linear detector array. Very similar to the data. The result is a set of "fan beam" data for each projection angle. In the present invention, once these data have been generated, they are fed to any suitable two-dimensional back projection algorithm, which allows the image to be displayed as if it were actual fan beam data. The slice can be reconstructed.

In the present invention, at each projection angle, the rows and columns of the detector array that receive their associated fan beam are identified before the actual scan is performed. In one embodiment, a simulation or calibration scan that simulates helical cone beam scanning of an opaque disk can be performed. At each projection angle, a simulated projection of the disk onto the array is recorded in the detected data. After the entire disk has been scanned, the projection data is analyzed to determine which rows and columns of the array receive the projection of the disk at each projection angle. The simulation process generates a “z-interpretation table” in which each projection angle is associated with a group of detection rows and columns to be read during subsequent scans of the actual object, Of fan beam data is generated. Once the desired slice has been reconstructed, the fan beam data at each projection angle is found from the associated array rows and columns stored in the z-interpretation table. In another embodiment, the actual opaque disk can be made helical cone beam scanning symmetric with the actual source and detector array to generate the z-interpolation table.

A number of fan beam projections are collected for each slice to be reconstructed. For example, in one embodiment, the data is a full half-turn of the gantry (1
80 °) + collected for angles subtended by the detector array. In one embodiment, the array is subtended at an angle of 60 °. Thus, each slice is generated from data collected during a 240 ° rotation of the gantry. In one embodiment, the projections are generated at every 1 ° projection angle. Thus, in this embodiment, each slice is generated from 240 fan beam projections. Groups of projections for successive slices along the z-axis can overlap each other. For example, a slice can be generated every 12 ° rotation. Thus, in the above embodiment, 228 of the 240 projections are shared by each pair of adjacent slices.

As mentioned above, in general, the reconstructed slice in the present invention is not a slice perpendicular to the z-axis as in conventional non-cone beam scanning. Instead, they are tilted or swiveled about the z-axis, and the normal axis of successive slices precesses about the z-axis. Each slice defines a slice plane having a longitudinal axis about which the scanning system rotates, ie, a normal axis that forms one angle with the z-axis. By using skewed slices, errors in the reconstructed slice data are reduced. The tilt angle can be determined using a simulation scan described above and described in further detail below. The selected angle is the angle at which the projection of the opaque disk onto the array produces the least image reconstruction error.

FIG. 5 is a schematic diagram illustrating data collection during a simulated scan for a single projection at a single angle, using slices of the tilted reconstructed image represented by the tilted opaque disk 132. FIG. X-ray cone beam 114 is emitted from source 110 and passes through an object (not shown) to illuminate a flat two-dimensional detector array 112. As shown, disk 1
The plane of the 32 slices forms an angle θ with an axis orthogonal to the z-axis. Equivalently, the normal axis to the slice plane forms an angle θ with the z-axis.

The projection of the ellipse of the tilted disk 132, ie, the shadow 130, is projected onto the detector array 112. As source 110 and detector array 112 rotate about the z-axis and move along the z-axis, projection 13 of disk 132
The location and shape of zero change. As the disk 132 moves through the scanning volume, or equivalently, as the source and detector are scanned through the slice, the area of the projected ellipse changes. As the disk 132 moves through the detector array, the tilt angle θ is fixed. The extent of the ellipse (its minor axis length) at each projection angle indicates the error introduced in the reconstruction of the slice at that projection angle. The purpose is to select a disk geometry that minimizes the total projected ellipse area over all of the 240 ° projection angles for the reconstructed tilted slice. Its area is minimized by reconstructing the tilted slice where the normal to the slice plane is tilted by a small angle θ.

FIG. 6 is a schematic diagram illustrating the relationship between the tilted slice 132 and the axes of the system. As described above, the normal 140 to the slice plane forms an angle θ with the z-axis, which is referred to herein as the tilt or swing angle. The normal axis 140 also forms the x-ray of the system, ie the horizontal axis and the rotation angle φ.

As described above, each slice has a projection angle of 0 ° to 180 ° + array angle (6
0 °). At 1 ° per projection, each slice is reconstructed from 240 projections. For any given slice, a particular slice tilt angle θ and rotation angle φ) will have the least error over all 240 projections. In one embodiment, adjacent slices are 1 from an overlapping set of 240 projections shifted by 12 °.
Reconstructed every 2 ° rotation. Each slice is associated with a tilt angle θ and a rotation angle φ that minimize reconstruction errors in that slice. In one embodiment, for successive slices, the tilt angle θ remains constant, and the rotation angle φ is the slice angle about the z-axis, as indicated by arrow 142 in FIG. The rotation angle φ is increased or decreased in order to define the rotation of the normal axis, ie, the precession. The error at each tilt angle is determined by summing the total area of the projections of all disks over the entire 240 ° data. The angle of inclination that produces the smallest total error is taken as the angle of inclination. In one embodiment, about 1
. A 45 ° tilt angle is used.

FIG. 7 is a schematic diagram showing the projection of the disk 132 at a tilt angle of 1.4 ° passing through the scanning area. This curve shows β = 0 °, 60 °, 120 °, 18
Shown are projections at 0 ° and 240 ° projection angles, or view angles. This figure assumes a flat detector array.

As described above, the detector array can be curved. In that case, the projection of the disk or slice onto the array is no longer an ellipse as shown in FIG. They are actually curved figures as shown in FIG. FIG. 8 shows the same projection as FIG. 7 at a tilt angle of 1.4 °. However, the detector array 112
Has a curved shape.

An example of the total projected area plotted as a function of the view is shown in FIG. The dashed line shows the area with a 1.45 ° tilt angle and the solid curve shows the area without a tilt angle. The tilt angle is selected as the angle that minimizes the total area, which in one embodiment is determined as 1.45 °.

As described above, simulated scans can also be used to identify the rows and columns of pixels used for each projection at each different projection angle. FIG. 10 is an example of the projection of a single tilted slice onto a curved detector array. All detectors on the array are read to identify the location of the projection 150, and therefore detector row and column locations to be read during future scans of the actual object at a particular projection angle. Read to identify. In this embodiment, the array includes 10 rows i of 252 detectors j each. Dotted line 150 indicates the extent of the curved elliptical projection on the array. Solid line 152 identifies the detector line that is read during subsequent scans at this particular projection angle. Line 152 is identified by calculating the value of the detector centroid across each row. It is this solid line 152 that defines the detector to be read during subsequent scans of the actual object. This process is completed at each projection angle for the slice to be reconstructed. The simulation or calibration process associates each projection angle with row and column values and stores them together in a "z interpolation table". This table is read on subsequent scans to identify the scan data used to reconstruct the actual slice. FIG. 11 shows a set of disk projections on a two-dimensional curved array for slices tilted at 1.45 ° in view angle between 0-240 °, each separated by 20 °. These are the row / column lines of the array generated for each projection angle during the calibration scan. Row / column numbers plotted for each projection angle are stored in the z interpolation table. The array used for this plot is a standard array consisting of 24 detector rows i of 252 detectors j each. As described above, each curve is identified by calculating the centroid of the projection on the array at each view angle.

After the simulated scan has been performed as described above to generate the z-interpolation table, the actual scan of the object can be performed according to the following procedure. First, projection data can be obtained by scanning a helical cone beam. The projection data can then be corrected for offsets, gain errors and non-linear effects. Next, the HCB data is applied to a z-interpolation process that extracts the desired fan beam data. At each projection angle, the detector row and column numbers are retrieved from the z-interpolation table and the X-ray intensity values at the identified detector rows and columns are recorded as fan beam data. In one embodiment, the z-interpolation process can proceed as follows. In each view, the process is performed stepwise through each detector j, one at a time. For each detector, the row number I is identified from the z interpolation table, which is generally some real number. If the row number i is not an integer,
Interpolation can be performed on the actual data value at the appropriate row number to identify the value for a particular detector as described below. In one embodiment, linear interpolation is used, but other forms of interpolation can be used.

For the rest of the reconstruction process, treat the interpolated data values as if they were fan beam values obtained during a conventional two-dimensional scanning procedure. Can be. They can optionally be applied to the reclassification process to generate parallel ray data. The reclassified two-dimensional data can then be applied to a conventional one-dimensional convolution procedure. Finally, the parallel convolved data can be applied to a conventional two-dimensional back projection algorithm. The above process is repeated for each slice in the region.

A mathematical description of the details of the scheme of the invention follows. Suppose a continuous cone beam data set is given by C (β, z ′, q). Where β is the gantry rotation angle (or view angle) or q and z ′ are positions on the detector as shown in FIG. In order to reconstruct one slice, the angular range of β must be at least 180 ° + fan angle. Reconstruction using the minimum number of projections is called half-scan. Let β _h be the range of projection angles used for half-scan reconstruction. More views are available if you need to correct for overscan. The method of overscan is described in detail below.

The NSR method can be summarized as follows. 1. For given β (where 0 ≦ β <β _h ), fan beam projection F (β, q) is extracted from cone beam data C (β, z ′, q). . The fan beam data is given by the following equation:

(Equation 1) Here, L (β, q) is a desired one-dimensional projection line (z ′ = L (β, q)). Optionally, F (β, q) can be reclassified to parallel data at this stage. This reclassification is a preferred method because back projection of parallel views is more computationally efficient than fan views. The reclassification procedure is described in detail below. 2. Convolve F (β, q) with the appropriate convolution kernel. 3. Backproject the convolved data using 2D-FBP. The method for determining L (β, q) and optimizing the tilt angle is described below.

In practice, cone beam data does not exist in a continuous form,
A method for secure implementation is used. Specifically, the data on line L (β, q)
The data must be determined by interpolation from discrete detectors.
Suppose the cone beam data is given by C [v, r, d]. here
, V is the view number (in the β direction) and r is the row number of the detector (in the z direction).
And d is the channel number of the detector in the given row (q
Direction). Also, if the limit value is 0 ≦ v <N_h, 0 ≦ r <N_rAnd 0
≦ d <N_dAnd Where N_hIs the number of views in the half scan, N _r Is the number of rows, N_dIs the number of detectors per row. Discrete variables
The relationship between and the continuous variable is as follows.

(Equation 2)

(Equation 3)

(Equation 4) Here, delta _beta is the angle between views, w _r is the distance between the row, w _d is the distance between detectors in a given row, r _c is z '= 0 for Is the row position, and _dc is the detector channel location for q = 0.

(Equation 5)

(Equation 6) As in the continuous case, the desired data exists along the line that intersects the ellipse. Let F [v, d] be fan beam data selected from C [v, r, d]. Interpolation in the r direction is called z interpolation. Let r '[v, d] be a look-up table that gives the location of the desired point in r for a given v and d. Fan data can be obtained by using linear interpolation at r. That is,

(Equation 7) Here, r ₀ is the largest integer value smaller than or equal to r ′, and p = r′−r ₀ .

The z-interpolation table can be determined by simulating projection data for a simulated tilted disk as described above. The simulated disk thickness is equal to the width of the detector row projected to the isocenter. The attenuation coefficient is constant over the entire disk, and the photon energy is monoenergetic. The given projection measured through the disk in this way is directly proportional to the thickness across. The center of the disk is at its isocenter and the fixed tilt angle is θ. The disk moves in the z-direction at the prescribed table speed of the scanner. Start and end of data collection (
That is, the position of the center of the disk at v = 0 and v = N _h −1) is symmetric about z = 0. The radius of the disc is equal to the scan radius R given by the following equation:

(Equation 8) Here, r _s is the distance from the source to the isocenter, δ is half the fan angle given me by the following formula.

(Equation 9) Where Δ _r is the angle between the detectors in a given row. The overall width of the detector in the z-direction at the isocenter is given by:

(Equation 10) Here, r _d is the distance to the detector from the source. The pitch p is defined as the ratio of table movement to D in 360 degree rotation of the gantry. That is,

[Equation 11] Here, _st is the speed of the table, and T is the rotation cycle of the gantry. For example, at one pitch, the table moves a distance D in one direction. The simulation can use the same geometry of the scanner. Alternatively, the simulation can use more detector rows to improve the resolution in determining the z-interpolation table. See Table 1. Table 1. Parameter values and definitions

As described above, the line of interpolation is determined by calculating the centroid in the row direction of the resulting projection data. Let m be the index of a simulation row.

(Equation 12)

The interpolation point m ′ [v, d] is given by calculating the centroid as follows.

(Equation 13) Next, the value of m '[v, d] is converted to a true detector row variable r' [v, d]. Here, (0 ≦ r ′ <N _r ). The z 'position of m' is given by:

[Equation 14] Here, mc is the position of the row at z ′ = 0, and w _m is the distance between detectors in a given row in the simulation. Next, the value of r 'is obtained by substituting equation (14) into equation (3) for z' and solving for r.
It is represented by the following equation.

(Equation 15)

The z interpolation table is a function of tilt angle, scanner geometry, and pitch. The pitch is fixed by the table speed, the gantry rotation speed, and the detector size according to equation (11). The tilt angle can be selected by the method described below.

Assume that the range of the view from the scanner is given by:

(Equation 16) By using a set of nh views, one slice is reconstructed. Steps 1-3 above are repeated for each slice for a different set of N _h views to reconstruct a series of adjacent slices. Let _{j be} the slice number in the series of N _j slices, where 0 ≦ j <N _j . Moreover, given slice j is to use the view _{v 0j ≦ v <v 0j +} N h, the first view for a given slice j and v _0j.

[Equation 17] Here, Δ _vj is a separation interval in a view between adjacent slices. The fan data for slice j is extracted from the cone beam data as follows.

(Equation 18) here,

[Equation 19] And 0 ≦ v _h <N _h . Note that the z interpolation table can be the same for each slice.

The plane of a tilted slice can be described by two rotations. The first rotation is due to the angle θ around the x-axis, and the second rotation is due to the angle φ around the z-axis. The equation of the plane of the swinging motion is given by the following equation.

(Equation 20) Where z ₀ is the location of the center of the plane in z (ie, in FIG. 6, z ₀ =
0).

In a series of slices, the precession angle φ is related to the view angle β. _Let the angle of the gantry corresponding to v _0j be _denoted as β _0j . The precession angle for slice j is given by:

(Equation 21)

Here, δ is a half of the fan angle as shown in FIG. 2, and is defined in Expression (9). Due to the geometry of the slicing slice, the separation between slices in z is a function of position in x and y, as well as pitch. Center (x, y) = (0
, 0), the position of z is given by:

(Equation 22) Here, _Δz0 is the separation distance of the slice at the isocenter, and is given by the following equation.

(Equation 23) Where N _v is the number of views per rotation. In general, the separation distance at any point (x, y) is obtained by solving equation (20) for z for two adjacent slices and taking the difference. That is,

(Equation 24) Δ _zj is sinusoidal and has a nominal separation distance at isocenter (constant)
Oscillate with respect to FIG. 12 shows that (x, y) = (0, 0), (R, 0), and (0,
, R) is the separation distance of the slice to the pixel in R, where R is the scan radius. Each point on the curve represents a different slice in the series of 36 slices. The slices are separated by ten views. (R, 0)
The curves for and (0, R) give the maximum amplitude. The pixels in R give a smaller amplitude at the separation distance of the slice.

Once the fan beam projection data has been selected for a given tilt angle, it can be reclassified into parallel beam projection data. One way of performing reclassification on continuous variables is disclosed in US Pat. No. Re 30,947, which is incorporated herein by reference. Here, reclassification is described as discrete data.

Reclassify fan data into 180 degree parallel data. As mentioned earlier, 1
The fan beam required to form an 80-degree parallel view is the gantry 18
Equal to the number of fan views contained in the rotation of 0 + 2δ degrees. If overscan correction is used, more fan views are needed, as described below. However, the reclassification procedure is the same whether or not there is overscan.

Reclassification can be performed in two steps by separating interpolation in the radial direction (q direction) and in the tangential direction (v direction). The relationship between the fan view and the parallel view is given by:

(Equation 25) Where β _p is the parallel view angle, β _f is the fan-view angle, and γ _f is the fan detector angle. _Let v _{p be} the index of the parallel view (0 ≦ v _p <N _p ) and v _{f be} the index of the fan beam (0 ≦ v _f <N _h ). The angle of the parallel beam is given by:

(Equation 26) Here, the delta _beta is the spacing view angle, [delta] is half the fan angle. For each view and fan detector d _f of parallel, interpolation points in the fan beam Ru is calculated.

[Equation 27] Here, γ [d _p ] is a fan detector angle given by the following equation.

[Equation 28] And where d _cf is the central fan detector. The hybrid parallel projection P _h [v _p , d _f ] is obtained by interpolation in the direction of the fan beam.

(Equation 29)

The interpolation in the radial direction is performed as follows. Let t be the location of the desired equally spaced parallel detector.

[Equation 30] Where w _diso is the spacing of the detector channels at the isocenter (in q units)
Where d _p is the number of parallel detector channels, (0 ≦ d _p <M _p ), and d _cp is the central parallel detector. The number of parallel detectors per view is given by:

(Equation 31) The position of t in the fan detector array is given by:

(Equation 32) The parallel projection P [v _p , d _p ] is obtained by interpolating the hybrid projection data at d _f .

[Equation 33]

The combination of z-interpolation and reclassification consists of interpolation of cone beam data in all three directions, v _f , d, and r. The interpolation of z can be performed first. Alternatively, it can be inserted into the reclassification procedure.

In stationary CT, parallel views must be symmetric over a 180 degree range. That is, views taken at 0 degrees and views taken at 180 degrees should contain the same information in the absence of motion due to symmetry. Movement of the object (or patient) breaks this symmetry, thereby
Discontinuities occur in the projection data for views separated by 0 degrees. As a result of this discontinuity, U.S. Patent No. 4,580,
Artifacts occur in reconstructed images that lead to the development of a correction scheme, such as the correction scheme described in US Pat.

Overscan correction is a method to smooth out the discontinuities and reduce motion artifacts. This is done by measuring the extra views and weighting them for convolution and backprojection. The number of extra views is usually small compared to the total number of views contained in π. Let N _os be the number of extra views so that the data set for the parallel view is 0 ≦ _vos <N _pos . Here, N _pos = N _p + N _os . The data is first multiplied by the weights to give weighted data.

(Equation 34) Here, the weight w is given by the following equation.

(Equation 35) Here, x ₁ and x ₂ are given by the following equations.

[Equation 36]

(37) After the weighted data is defined, there are at least two ways to proceed. Let P _out be the parallel projection of the output that is convolved and back-projected. In a first method, the projection of the output is equal to the weighted projection. That is, it is given by the following equation.

(38) And the number of views is _Npos . In the second method, the projection of the output is given by:

[Equation 39] here,

(Equation 40)Where 0 ≦ v_os<N_pIt is. The number of output views in the second method is less than in the first method. Initially, a smaller number of backprojected views is advantageous in terms of computational efficiency.
It may look like. But in a pipelined architecture,
, The first method may be more efficient. This is because in the second method N _p This is because the two views separated only by the sum are added to each other. Save one view to add to another view collected at a later time
That may not be possible in a pipeline. These two methods are the same final
Generate an image.

As mentioned above, each slice of the swing used to create an image in accordance with the present invention is reconstructed from projection data acquired at multiple projections or view angles. In one embodiment, a total of 240 projections or views are taken at 240 °, one projection or view at a time, to obtain sufficient data to completely reconstruct the slice. In one embodiment, the data for successive slices is separated by 12 °, resulting in overlap between adjacent slices of 228 projections. As described above, each projection taken in each view is, in one embodiment of the present invention, reclassified into parallel ray data before it is reconstructed into image data for the slice. -It can be considered as beam projection.

Further, according to the present invention, a projection image of an area scanned from a single angle is generated by using the reclassified projection data. This two-dimensional projected image is similar to what would be obtained if the area were scanned by gentle rotation while the source and detector were moved along the longitudinal axis of the area. ing. This is similar to images obtained by stationary X-ray line scanners that obtain image data only from a single angle through the area being scanned.

In the present invention, projection images are collected during scanning as described above, where the source and detector can be rotated around the object and spiraled as it moves along the object. A projection image can be generated from the reconstructed parallel ray data obtained from the projected projection data. In the present invention, a projection angle for a two-dimensional projection image is selected. For example, from top to bottom,
It may be desirable to create a projection image of the area as viewed vertically. In that case,
The selected projection angle is 0 °. In other embodiments, it may be desirable to view the object from the side. Therefore, the selected projection angle is 90 °. In other situations, it may be desirable to view the area from several different angles. In that case, multiple projection angles, eg, 0 °, 120 ° and 24 °
One can select 0 ° so that the area can be seen from evenly spaced angles.

Given a selected projection angle, data is selected from the reclassified fan beam projections to generate a two-dimensional image. In one embodiment, for each slice, a single projection or view taken from a single corresponding view angle is selected. The selected view angle for one slice is the angle corresponding to the selected projection angle for that projection image. For successive slices,
The views used in the projected image are different. For example, in the described embodiment of the present invention, adjacent slices are separated by 12 views,
The reclassified view data selected for adjacent slices, corresponding to the same preselected projection angle, will be offset by 12 views. That is, for example, if the view corresponding to the selected projection angle is the 30th view within one slice, the view selected from the next adjacent slice is the 18th view. Become. One view is identified,
After being selected for each slice to be used for the projection image, the selected view data is combined to generate a two-dimensional image of the region from the selected projection angle.

One conventional method for collecting projection images in CT is through a gantry.
Scanning the object without rotating the gantry while moving the object
You. In the present invention, the projected image is the swing obtained while the gantry is being rotated.
Extracted from the slice projections. To illustrate, each slice has a fixed increment
Assume that they are separated by an angle. Therefore, the corresponding in adjacent slices
View angles are constant Δ_vOnly the views can be considered to be separated from each other. For example, in one embodiment, Δ_v= 12 views. The first view angle in each slice is Δ Δ from the first view angle in the next slice._v Only the view is separated. The second view angle in each slice is
From the second view angle in_vOnly the view is separated. The same applies hereinafter. The first parallel projection is the view v₀Let's say In the next slice, v₀+ Δ _v Is selected. This process continues for any desired length or until there are no more slices. Combine selected views
As a result, a parallel projection image at a fixed view angle is obtained. Projection image swings
Note that it is a type. Because the data is swing type projection data
This is because they have been selected. Final projection image interpolated parallel if necessary
can do.

[0083] Each slice may be considered to be formed from the integers N views v _i. Here, i = 1,. . . , N. In one embodiment, N = 240 as described above. For each slice j, there is one view vi _{, j} containing the data corresponding to the preselected projection angle, and for the next adjacent slice, j + 1, There is one view v _{i + Δ v, j + 1} that contains data for slice j + 1 corresponding to the selected projection angle. Thus, the view v _{i + 1,} which is selected from a slice j + 1 which is next adjacent is given by _{v i + 1 = v i +} Δ v.

FIG. 14 pictorially illustrates the occurrence of a two-dimensional image projection of the present invention. In one embodiment, the view for the projection image is selected from the data reclassified for parallel geometries. As shown in that figure, the reclassified parallel data for each view in the projection of the image effectively includes a series of parallel lines or samples 249 at the projection angle. In this case, the selected projection angle ψ is selected as 30 °. That is, it is desirable to create a two-dimensional image of the scan area 247 viewed through the area at a 30 ° angle. Thus, each slice generated according to the above description has a set of reclassified, parallel, taken from the corresponding view angles that will provide data for a 30 ° view through the region. There is a single projection or view that contains the data 249. In the embodiment described here, assume that the slice starts at 0 ° relative to the first slice and the 30th view is selected. Since the view provides data corresponding to a 30 ° projection through the area. The eighteenth view is selected for the second slice. For the third slice, the sixth view is selected. 174 for the next slice
The second view is selected. This explains that instead of collecting the entire 360 ° data for each slice, only 180 ° + twice the fan angle, ie 240 ° data, is obtained. Thus, scan data is used for light rays passing through an area in the opposite direction to the light rays of the immediately advancing slice. Furthermore, because the rotation around the central axis 18 causes the 180 ° detector array to be skipped relative to the previous slice, the order of the detector data in the selected projection must also be skipped. No. That is, d _i = d _Ni . Where d represents the data from detector i and N is the number of detectors in one view.

This process is repeated until all projections corresponding to the preselected projection angle of 30 ° have been identified for each slice to be used in the projection image, May continue for only as many slices. The data is then combined to produce a projection looking through the area at a preselected angle of 30 °. It should be understood that not all of the slices need be used to generate that image. To improve the throughput, the slice can be omitted from the projection angle, and the appropriate adjustments can be made to the delta _v.

The data used to generate these projections is typically collected by a first scan, so that the data can be processed to create projections from any angle. Further, multiple angles can be selected. This may be useful where it is desirable to view the area from different angles to identify suspicious objects within the area. For example, it may be difficult to identify a prohibited item such as a pistol using a view from only a single angle. But,
If multiple projections are created, the pistol can be more easily identified. Thus, processing of the projected image can be used as a pre-screening process to identify suspected luggage in baggage scanners. The image data for the suspected luggage can then be completely reconstructed and, if necessary, a full three-dimensional image of the luggage can be generated.

In the CT scanning system of the present invention, and in other conventional systems, each slice is a volume element of a set of images, or “voxels”.
Is defined. In conventional CT systems, these voxels are oriented so that their axes are parallel to the corresponding coordinate axes in the field of view in the CT system. However, in the system of the present invention, as described above, the slice is oscillating or tilted, and its volume element is tilted with respect to the axis of the CT scanning area.

One application of the CT scanning system of the present invention is in a commercial aircraft luggage scanner as described above. One function of the baggage scanner of the present invention is to identify target materials, such as explosives, by analyzing the scan data of the materials collected by the system. One method for identifying explosives is to compare the density values of the image for the material obtained by scanning with the density values of the material of a known explosive. An inspection can then be performed to further analyze the item.

One important factor in scanning for explosives and determining the potential hazards they present is the total mass of the explosive. In the present invention,
The total mass can be calculated by multiplying each density value of each voxel associated with the explosive by its volume. The mass of the individual voxels is added from the voxels of the density identified as likely to be the density of the explosive to determine the total mass of the explosive.

As described above, in an NSR system, the voxels are tilted with respect to the scan axis of the system. This results in a small error when calculating the mass associated with one voxel. In the present invention, a sloped voxel can be interpolated for a non-slant density value, or a correction factor can be calculated to correct for a slope in the voxel. Either method provides a function to more accurately determine the total mass of the suspicious object. Details of these methods are described below.

A reference frame of the object of the CT slice being reconstructed, scanned, and oscillating by the NSR is shown graphically in FIG. The reference fixed frame in which the object is defined is in xyz space, and the reference frame for the tilted slice is defined by x'y '. The origin of the inclined slice is in the z _0. The angle of the swing motion is θ, and the angle of the precession is φ. The swing angle is amplified in this figure to emphasize the swing and tilt of the reconstructed slice. In practice, the swing angle is small enough, such that cos θｓ1 and sin θ ≒ 0.

Let f (x, y, z) be the continuous objective function to be reconstructed. The spatial extent of the objective function is | x ² + y ² | <R, and | z | <∞. Here, R is a scanning radius. The scanner rotates around the z-axis. For the purposes of this description, it is assumed that the scanner is moving along the z-axis and is also rotating. Actually, an object can be moved instead of the scanner.

The NSR reconstructs a series of two-dimensional (2D) slices. Coordinate system of the 2D slices are x'y 'plane, the origin of the space is in z ₀ along the z-axis as shown in Figure 13. The 2D slice is swung by θ from the z axis. Note that the swing occurs with respect to the origin z ₀ . The angle of the precession of the head is given by φ, where φ is measured with respect to the z-axis. The swing is performed around a new x-axis formed by rotating about the z-axis by φ.

Let f ′ (x ′, y ′; z ₀ ) be a slice of a continuous objective function in the swing space at z ₀ . The relationship between slices in each x'y 'plane and xyz space can be determined by rotating the coordinate system. In particular, includes a first rotation about φ about the z-axis, followed by a second rotation about θ about the new x-axis, and a final rotation about 新 し い = −φ about the new z-axis. It can be obtained using a rotation matrix. These three rotations are denoted as R _z (φ), R _x (θ), and R _z (Ψ), respectively. The rotation is given by the following matrix:

[Equation 41]

(Equation 42)

[Equation 43] The product B of these three rotations is given by:

[Equation 44] In practice, θ is small enough that cos θ ≒ 1. Using this approximation and the relationship Ψ = −φ, equation (44) becomes:

[Equation 45] The relationship between the reference frames is given by:

[Equation 46] Equation (46) shows that the x 'and y' axes map directly to the x and y axes, respectively. However, the z axis is the position of x′−y ′, the angle of the precession φ,
Compression or expansion depending on the angle θ of the swing motion. Therefore, equation (4)
The following equation holds for the conversion given in 6).

[Equation 47] The relationship between the x'y 'coordinate system and the xyz coordinate system is defined by each slice (
(Indicated by the value of z ₀ ).

The coordinates and interpolation sampling used to generate the parallel slices are described below. Suppose we need an infinite set of parallel slices, each slice consisting of NxN pixels. The slices are spaced along the z-axis by δ _z . Let k be the index of a parallel slice or the slice number. Here, -∞ <k <∞. Let i and j be the sample indices along the x and y axes, respectively. here,
0 ≦ i <N and 0 ≦ j <N. Let the sampled slice be F (i, j,
k). The sampled and continuous function is related as follows:

[Equation 48]

[Equation 49] Here, the pixel size δ _xy is 2R / N. Note that other definitions for x and y can be used. For example, the pixel size is δ _xy = 2R / (N
-1) or a reconstruction field smaller than the scanning field of view 2R can be used.

A similar relationship can be written for images in the headspace. The sampled swing space is given by F (i ', j'k'), where the following equation is given.

[Equation 50]

(Equation 51) Here, i ′ and j ′ are sample indices along the x ′ axis and the y′-z ′ axis, respectively. The index k 'is a sample index of the slice which is inclined corresponds to the z _0. The range of the index is 0 ≦ i ′ <N, 0 ≦
j ′ <N and −∞ <k ′ <∞. The parameter δ _{z ′} is the z-axis spacing between heading slices and is generally not equal to δ _z ′. φ _{k '} for each slice k
Let 's be the angle of precession to'. here,

(Equation 52) And

(Equation 53) It is. And finally, z _r is the non-linear distance per 2φ of rotation, and φ ₀ is the phase offset to the precession angle determined by the starting angle of the scanner. Without loss of generality, assume that φ ₀ = 0. The variable M is used to describe the number of images per rotation. This is given by the following equation:

(Equation 54) Here, the following equation is established.

[Equation 55]

[Equation 56]

[Equation 57]

[Equation 58] Here, k is given by the following equation.

[Equation 59] Here, x ′ and y ′ are given in equation (51). The last equation (59) is k
'Is nonlinear with respect to Newton-Raphson (Newton-Ra)
(Phson). Alternatively, the values of g (i, j, k ') for a given value of k' can be tabulated for each i and j value. The value can be searched to find the value of k 'that puts the desired value of k in parentheses. In practice, k ′ may not be an integer, and equation (55)
Is replaced by interpolation between adjacent values of k '. Linear interpolation can be used.

After correction for heading, the collection of slices is denoted by F (i, j, k), where i and j correspond to sampling in the image plane (ie, xy plane) and k Corresponds to sampling in the axial direction (ie, the z-direction). The pixel size in the plane is _δxy . The sampling distance in the axial direction is δ _{z '} . Therefore, the volume of each voxel is δ ² _xy δ _{z ′} . Function F (i, j, k
) Represents the density of the object, the mass of the voxel at (i, j, k) is δ ² _xy δ _z F (i, j, k).

One purpose of explosive detection is to determine the mass of a potential explosive in a scanned object. Procedures are implemented to determine which voxels are part of the explosive. An exemplary method for this procedure is a connected component labeled (CCL). The output of this procedure is a binary "window" function W (i, j, k), which indicates whether the voxel at (i, j, k) is part of an explosive. Therefore,

[Equation 60] The mass of the explosive, _Me, is given by:

[Equation 61]

Here, the case of the swing slice according to the present invention will be considered. As noted above, they are denoted by F '(i', j ', k'). The dimensions in the plane are again given by _δxy . However, the axial position of each slice, z _{k ′,} is given by:

(Equation 62)Here, x ', y', and c are defined above. (I ′, j ′, k ′) Δ _{k '} The spread of the axis of the voxel at the position is approximated as follows.

[Equation 63]

The same procedure for determining which pixel the explosive part used for parallel slices is can be used for head slices. Therefore, CCL can be used. The output of this procedure is a binary window function W
'(I', j ', k'), which indicates whether the voxel at position (i ', j', k ') is part of an explosive. The mass of the explosive is given by the following equation (6)
It can be obtained using 4).

[Equation 64]

One advantage of equation (64) over equation (61) is that F ′ (i ′, j ′, k ′)
And the interpolation between F (i, j, k) is eliminated. Interpolation increases the partial volume artifacts that can reduce the density value of thin explosives. This reduction in density complicates the task of determining which voxels are part of the explosive.

In another aspect of the present invention, a parallel processing architecture is employed to generate and process swiveling image data slices of the present invention, compared to those obtained in conventional pipeline processing systems. Provides much more efficient processing. As a result of the improved efficiency provided by the parallel processing architecture, the efficiency of image generation is greatly improved, thus applying this system to high scanning throughput settings such as the airport luggage scanner of the present invention. be able to.

FIG. 15 includes a schematic functional block diagram of a serial pipeline method for generating and processing swing slice data according to the present invention. In this system, a data acquisition system (DAS) 300, which includes an array of radiation sources and detectors, acquires the scan data and transfers them to a data correction process 302. The data correction process corrects the data to correct for air detector readings, detector temperature offsets, detector nonlinearities, and general imperfections in the system. Add. Subsequent to the correction 302, the scan data is forwarded to the generation 304 of the reconstructed data of the pivoting slice, which, as described in detail above, uses the fan data from the set of projection data in the scan data. Extract the beam projection. The generated fan beam projections can then be applied to an optimal reclassification process 307 to generate a reclassified parallel beam projection from the fan beam projections. For each slice, the projection of the fan beam or the re-sorted parallel beam is transferred to a filtering process 306, which filters the projections and then returns to the backprojection process 308. The backprojection process 308 generates image data for the slice. Finally, the slice image data is used to generate image 310.

The pipeline approach suggests that slices are generated and backprojected at once from the scan data collected by DAS 300. However, in practice, as described above, each set of projection data from each individual view is used to generate projections for a plurality of adjacent slices. This is due to the overlap of slice data in successive or adjacent views. In the above embodiment, each slice is generated from scan data collected in 240 discrete views. Therefore, for each slice,
At each of the 240 locations around the longitudinal axis, a single fan beam projection is extracted from the entire set of projection data collected at that location. But,
As described above, each slice is separated by 12 ° of view rotation. As a result, there is considerable overlap of scan data on many slices.
That is, scan data collected at one particular view angle is used to generate many slices. For example, in the above embodiment, each slice uses 240 views separated by 1 °, and the slices are separated by 12 ° rotation, using each set of projection data in a single view, Twenty slices can be generated. In practice, each view actually contributes to 22 slices in one embodiment, due to effects at the end of the data stream.

As a result of this overlap, the NSR 304 shown in FIG. 15 actually generates projections for many slices, for example, 22 slices simultaneously. That is, instead of generating a single projection for a single slice in each of the 240 views, 22 projections in each of the 240 views are actually generated. This may cause a large processing load in the configuration of the pipeline processing.

FIG. 16 is a schematic functional block diagram illustrating a parallel configuration according to the present invention that can be used to generate and process the projections used to generate the swing slice of the present invention. . Again, DAS 300 generates scan data that is corrected by data correction process 302 before being transferred to NSR process 304A. In this configuration, the NSR process is performed by a single processor 305.
The processor 305 analyzes the scan data to generate the fan beam projections necessary to generate a swiveling slice. At each projection angle, processor 305 generates a projection of the fan beam for each slice for which the projection data under consideration contributes to the data. In general, as described above, each set of projection data contributes to a number of slices, eg, 22 slices, and thus a number of projections are generated. In this embodiment of the invention, each slice generated is associated with its own data storage element or memory 312. In the embodiment shown in FIG. 16, since each set of projection data can contribute to up to 22 slices, there are 22 memories 312A used to store the generated projections. There are ~ 312V.

[0107] In each view, processor 305 generates one projection for each slice. The projections generated for one slice are transferred and stored in the memory element 312 associated with that slice. In general, if 22 slices are being generated simultaneously, 22 projections will be generated from each view, and 2
It is stored in two respective associated memories 312.

The generation of this projection and the storage in the pre-allocated memory continues until all data has been processed. A single slice is completed for all 240 views. That is, all of the projections for a slice have been generated and stored in their respective associated memories. Memory element 31
When 2 is thus full, the projection stored in the memory element (as needed to generate a single slice) is transferred to multiplexer 314, which provides the projection for that slice. Select the memory you are using. The entire set of projections for that slice can then be forwarded to an optional reclassification process 307, which can reclassify the fan beam projections into parallel beam projections. Next, the filtering process 306
Can be performed on the data, and then backprojection 308 can be performed to generate image data for the swiveling slice. After the slice is generated,
An image 310 can be created.

The process of filling memory 312 with projections continues throughout all views for which the scan data has been acquired. Since the slices are separated by 12 views in one embodiment, for all 12 views processed, one of the memories 312 is filled with the required 240 projections for the slice. In the next view, the memory filled in the previous view starts to be filled again with projections from another slice to be processed. Thus, if the slice is, for example, 12
If separated by one view, the generation of projections for one slice is completed every 12 views. Thus, for example, for slices separated by twelve views, the generation of a projection for one slice is completed for every twelve views. Thus, for every twelve views, each memory element 312 is filled. In the next view, the memory element starts collecting elements for the new slice.

With this configuration, the projection data of the slice is processed very efficiently. While the projections are generated simultaneously for multiple slices, the actual slices are reclassified, filtered and backprojected one at a time.

FIG. 17 is a schematic functional block diagram of another embodiment of the present invention using a parallel configuration for generating and processing a swing-type slice of the present invention using a parallel configuration. is there. In the embodiment shown in FIG. 17, the parallel memories 312A-3
12V is used in the same manner as described above with respect to FIG. 16 to store the projection of the fan beam for each slice as they are collected. However, the configuration includes a plurality of processor stages 304B, including a plurality of data correction stages 302A-302H respectively coupled to a plurality of NSR processing stages 305A-305H. Scan data is received from DAS 300 by demultiplexer circuit 320, which forwards the data to a selected 302/305 data correction and swing slice processing stage. Each stage 302/30 of the correction / swinging slice process
5 receives data for a single view from the demultiplexer 320. It analyzes the set of projection data from that single view and generates a projection of the fan beam on each of the slices for which a particular view contributes to the projection data.
The generated projection is then transferred to a memory 312 associated with the slice that uses the generated projection. Once again, in the example described here, each view contributes to a single projection for each of the 22 slices, and thus the processor 305 converts 22 projections to 2 for each view or set of projection data.
Transfer to two memory elements 312A to 312V.

In the embodiment shown in FIG. 17, eight swivel slice correction / processing elements 302/305 are used. It should be understood that different numbers of processing elements can be used. The demultiplexer 320 determines that the set of projection data for each view is DA
Cycle through eight elements each time it is received from S300. This provides some level of parallelism for scan data processing, and therefore greatly increases the speed at which processing can be performed. This is very useful in settings such as luggage scanners where high scanning throughput is required.

As shown in FIG. 17, all of the swing slice elements can send projections to any of the memory elements 312. In other embodiments, each processor 305 can only communicate with a portion of memory element 312. This method can be used to simplify communication between the processor 305 and the memory 312, and also to resolve contention for the memory 312.

In one embodiment, memory element 312 is full of projections for one slice when it contains 240 projections. The full set of projections is transferred via multiplexer 314 to optional reclassification process 307. After the fan beam projections have been reclassified into parallel beam projections, they are filtered by 306 and backprojected by 308 into image slices. The slice can then be used to generate an image 310.

In one embodiment, the process of reclassification 307 is
Can be implemented in In that embodiment, when data reclassification is required, one of the processors 305 is instructed to perform the reclassification.
After the processor has been commanded to perform reclassification, and that processor has completed the current task of producing the projection of a particular view, instead of processing the next view,
The processor is temporarily suspended, and it can perform the requested reclassification function. When the reclassification process is completed, the processor rejoins the other processors in the cycle of processing the projection data. In one embodiment, any processor may be instructed to perform reclassification at any time. This method for sharing processors eliminates the hardware complexity in the system by reducing the number of processors and associated circuits in the system.

The present invention has been particularly shown and described with reference to preferred embodiments, but those skilled in the art are defined in the following claims. It is to be understood that various changes may be made in form and detail without departing from the spirit and scope of the invention.

[Brief description of the drawings]

The above and other objects, features and advantages of the present invention will become apparent from the above more detailed description of the preferred embodiments of the invention, as illustrated in the accompanying drawings. In the drawings, like reference numbers indicate the same parts throughout the different views. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the invention.

FIG. 1 is a schematic axial view of a typical prior art computed tomography (CT) scanner.

FIG. 2 is a schematic diagram illustrating a projection angle and a detector angle of a CT scanning system.

FIG. 3A shows a scanning path for a constant z-axis (CZA) scanning mode in a CT scanner.

FIG. 3B shows a scanning path for a constant speed helical (CSH) scan in a CT scanner.

FIG. 4 is a simplified schematic diagram showing the spatial relationship between sources, detectors and scanned objects in a CT scanner according to the present invention.

FIG. 5 is a simplified schematic diagram of the projection of a tilted slice onto a two-dimensional detection array.

FIG. 6 is a simplified schematic diagram illustrating the tilt and rotation angles of a tilted slice according to the present invention.

FIG. 7 is a simplified schematic diagram of the projection of a tilted slice onto a flat detector array.

FIG. 8 is a simplified schematic diagram of the projection of a tilted slice onto a curved detector array.

FIG. 9 includes a schematic plot of the total projected area of tilted and vertical slices versus view angle.

FIG. 10 is a simplified schematic diagram of the projection of a slice onto a curved detector array.

FIG. 11 is a simplified diagram showing the projection of a slice on a two-dimensional curved array for projection angles from 0 ° to 240 ° in 20 ° increments.

FIG. 12 is a schematic plot illustrating slice separation in the z-axis direction according to the present invention.

FIG. 13 is a graphical representation showing the relationship between a reference frame for an object being scanned and a swiveling image data slice generated in accordance with the present invention.

FIG. 14 is a schematic diagram illustrating the generation of a two-dimensional projected image according to the present invention.

FIG. 15 is a schematic functional block diagram illustrating the generation and processing of swing slice data according to the present invention using a method of pipeline processing.

FIG. 16 is a schematic functional block diagram illustrating the generation and processing of swiveled slice data according to the present invention using a single processor parallel memory processing scheme.

FIG. 17 is a schematic functional block diagram illustrating the generation and processing of swiveled slice data according to the present invention using a parallel memory scheme with multiple parallel processors.

[Procedure amendment]

[Submission date] September 27, 2000 (2000.9.27)

[Procedure amendment 1]

[Document name to be amended] Statement

[Correction target item name] Claim 1

[Correction method] Change

[Correction contents]

[Procedure amendment 2]

[Document name to be amended] Statement

[Correction target item name] Claim 7

[Correction method] Change

[Correction contents]

[Procedure amendment 3]

[Document name to be amended] Statement

[Correction target item name] Claim 14

[Correction method] Change

[Correction contents]

[Procedure amendment 4]

[Document name to be amended] Statement

[Correction target item name] Claim 24

[Correction method] Change

[Correction contents]

[Procedure amendment 5]

[Document name to be amended] Statement

[Correction target item name] Claim 34

[Correction method] Change

[Correction contents]

[Procedure amendment 6]

[Document name to be amended] Statement

[Correction target item name] Claim 44

[Correction method] Change

[Correction contents]

────────────────────────────────────────────────── ─── Continued on the front page (31) Priority claim number 08 / 948,697 (32) Priority date October 10, 1997 (Oct. 10, 1997) (33) Priority claim country United States (US) ( 81) Designated countries EP (AT, BE, CH, CY, DE, DK, ES, FI, FR, GB, GR, IE, IT, LU, MC, NL, PT, SE), OA (BF, BJ, CF, CG, CI, CM, GA, GN, GW, ML, MR, NE, SN, TD, TG), AP (GH, GM, KE, LS, MW, SD, SZ, UG, ZW), EA (AM, AZ, BY, KG, KZ, MD, RU, TJ, TM), AL, AM, AT, AU, AZ, BA, BB, BG, BR, BY, CA, CH, CN, CU, CZ, DE, DK, EE, ES, FI, GB, GE, GH, GM, HR, HU, ID, IL, IS, JP, KE, KG, KP, KR, KZ, LC, LK, LR, LS, LT, LU , LV, MD, MG, MK, MN, MW, MX, NO, NZ, PL, PT, RO, RU, SD, SE, SG, SI, SK, SL, TJ, TM, TR, TT, UA, UG, UZ, VN, YU, ZW (72) Inventor Bailey, Eric United States. 03841 New Hampshire, Hampstead, Wheellight Road 193 (72) Inventor Greenberg, Alexander, I. United States. 02135 Massachusetts, Brighton, Lake Shore Road No. 1 104 (72) Inventor Ruth, Christopher, Sea. 01923 Massachusetts, Danvers, Locust Street 34 F-term (reference) 4C093 AA22 AA29 BA03 BA10 CA01 CA13 CA18 CA32 EB17 ED07 FD07 FD09 FD11 FD12 FE01 FE06 FE12 FE13 FE14 FE15 FE26 FF01 CE04506 CE

Claims (50)

[Claims] 1. A method of processing computed tomography scan data for an area having a longitudinal axis, the method comprising: scanning the area with an array of radiation sources and detectors; Generating the scan data; defining a plurality of image data slices corresponding to a plurality of positions along the longitudinal axis of the region, wherein successive image data slices are not parallel to one another. And a slice of the image data, wherein each slice of image data defining a volume element of the plurality of images is inclined with respect to the longitudinal axis, and wherein each image volume element is associated with a density value of the image. Defining, and applying a correction factor to the image density value of the sloping volume element, Correcting for the elemental tilt. 2. The method of claim 1, further comprising processing density values of the image to determine a mass of an object in the region. 3. The method of claim 2, wherein the step of processing the density values of the image to determine the mass of an object in the region comprises the step of: Applying the method. 4. The method of claim 3, wherein a density value that exceeds the density threshold is used to determine a mass of the object, and a density value that does not exceed the density threshold is the object. A method that is not used to determine the mass of a. 5. The method of claim 3, wherein a density value of the image that exceeds the threshold is considered to be associated with an explosive material. 6. The method according to claim 2, wherein the object comprises an explosive substance. 7. An apparatus for processing computer tomography scan data for an area having a longitudinal axis, the apparatus scanning the area and providing the scan data for the area. An array of detectors to generate, and a plurality of image data slices corresponding to a plurality of positions along the longitudinal axis of the region, wherein successive image data slices are parallel to one another. And each image data slice defines a plurality of image volume elements that are inclined with respect to the longitudinal axis, and a processor that causes each image volume element to be associated with an image density value; and a correction factor. Means for applying to the image density value of the sloping volume element to correct for the skew of the image volume element. Device. 8. The apparatus according to claim 7, further comprising means for processing said image density values to determine a mass of an object in said region. 9. The apparatus according to claim 8, wherein said means for processing said image density to determine the mass of an object in said region comprises a density threshold for said image density value. Apparatus including means for applying. 10. The apparatus of claim 9, wherein a density value that exceeds the density threshold is used to determine the mass of the object, and a density value that does not exceed the density threshold is the density value. A device that is not used to determine the mass of an object. 11. The apparatus according to claim 9, wherein an image density value exceeding the threshold is considered to be associated with an explosive substance. 12. The apparatus according to claim 8, wherein said object comprises an explosive substance. 13. The apparatus according to claim 7, wherein said array of radiation sources and said detector is rotated about said longitudinal axis of said region, while being rotated about said longitudinal axis of said region. An apparatus comprising means for moving the source of radiation and the array of detectors along. 14. A method of processing computed tomography scan data for an area having a longitudinal axis, the method comprising: scanning the area with an array of radiation sources and detectors; Generating the scan data, wherein the scan rotates at least the source of radiation about the longitudinal axis through a plurality of view angles while the source of radiation directs radiation toward the array of detectors; Scanning data comprising a plurality of sets of projection data respectively collected at the plurality of view angles; and slice data for the plurality of image data slices of the region from the plurality of sets of projection data. And each set of projection data generates a plurality of image data slices. Wherein each image data slice is generated from a projection from each set of a plurality of projection data, wherein the generation of the slice data comprises, for each image data slice, Associating a slice with a data storage element; storing in the data storage element the projection to be used to generate the slice data for the image data slice; Processing the projected projections to generate the slice data. 15. The method of claim 14, further comprising: filtering the projection stored in the data storage element to generate the image data slice for the region. 16. The method according to claim 14, wherein the projection stored in the data storage element is backprojected to generate the image data for the region.
A method further comprising generating a slice. 17. The method of claim 14, further comprising providing a plurality of processors to generate the plurality of projections from each set of projection data. 18. The method of claim 14, wherein each image data slice to be generated is associated with one of the plurality of processors, and among the plurality of processors associated with the one image data slice. Generating the projections on the image data slices. 19. The method of claim 18, wherein one of the plurality of processors is used to reclassify the fan beam projection into a parallel beam projection. 20. The method of claim 18, wherein one of the plurality of processors reclassifies the fan beam projection for a first image data slice into a parallel beam projection. A method, wherein another of said plurality of processors is adapted to generate a projection of a fan beam onto another image data slice from a set of projection data. 21. The method of claim 14, wherein the image data slices are not parallel to one another. 22. The method of claim 14, wherein successive image data slices are oscillating with respect to each other. 23. The method according to claim 14, wherein the image data slice is tilted with respect to the longitudinal axis. 24. An apparatus for processing computed tomography scan data for an area having a longitudinal axis, the apparatus comprising: an area for generating the scan data for the area; An array of radiation sources and detectors for scanning the plurality of projection data; and receiving each of the plurality of projection data such that each image data slice is generated from one projection from each set of projection data. Multiple image data
A processor for generating, from each set of projection data, a plurality of projections used to generate a slice; and a data storage element associated with each image data slice, wherein at least a plurality of sources of the radiation are provided. Rotated about the longitudinal axis through the view angles of the beam, while the source of radiation directs radiation toward the array of detectors, and the scan data is collected at each of the plurality of view angles. A plurality of sets of projection data, each data storage element storing a projection used to generate said respective associated image data slice, and wherein said processor stores said storage from each data storage element. Processing the projected projections into slices for the image data slices associated with the data storage element. In which device adapted to generate the over data. 25. The apparatus of claim 24, further comprising a filtering subsystem for filtering the projection stored in the data storage element. 26. The apparatus according to claim 24, further comprising a back projection subsystem for backprojecting said projection stored in said data storage element. 27. The apparatus of claim 24, further comprising a plurality of processors for generating said plurality of projections from each set of projections. 28. The apparatus according to claim 27, wherein each image data slice to be generated is associated with one of the plurality of processors and the plurality of image data slices are associated with one image data slice. An apparatus wherein one of the processors is adapted to generate the projection on the image data slice. 29. The apparatus of claim 27, wherein one of the plurality of processors is used to reclassify the fan beam projection into a parallel beam projection. 30. The apparatus of claim 27, wherein one of the plurality of processors reclassifies the fan beam projection to a first image data slice into a parallel beam projection, while An apparatus wherein another one of the plurality of processors is adapted to generate a projection of the fan beam from one set of projection data to another image data slice. 31. The apparatus according to claim 24, wherein the image data slices are not parallel to one another. 32. The apparatus according to claim 24, wherein successive image data slices are oscillating with respect to each other. 33. The apparatus according to claim 24, wherein the image data slice is tilted with respect to the longitudinal axis. 34. A method for generating a two-dimensional projected image of an object in a region having a longitudinal axis, the method comprising: generating a scan data representative of the region; Scanning, comprising: providing a source of radiation and an array of detectors located opposite the area; wherein the source of radiation is directed toward the array of detectors. Rotating at least the source of radiation about the longitudinal axis while irradiating the array; receiving radiation from the region by the array of detectors and generating the scan data for the region; The method further comprises defining a plurality of data slices of the image corresponding to a plurality of locations along the longitudinal axis of the region. Successive image data slices are not parallel to one another, each of said image data slices defining a plurality of scan data projections obtained from a respective plurality of view angles during said step of scanning. And wherein the projection of each scan data includes scan data at a respective view angle, the method further comprising: selecting an angle with respect to the two-dimensional projected image of the region; Identifying, for each of the slices, the view angle corresponding to the selected projection angle; and for each of the image data slices, the scan data corresponding to the identified view angle. Selecting a projection of the region, and generating a two-dimensional projected image of the region using the projection of the selected scan data. Tsu method comprising the-flops. 35. The method of claim 34, wherein the array of detectors is also rotated about the longitudinal axis to scan the area. 36. The method of claim 34, wherein the step of scanning the region comprises rotating the source of the radiation at least about the longitudinal axis of the region while longitudinally rotating the region. The method further comprising moving the object relative to the source of radiation and the array of detectors along an axis. 37. The method according to claim 34, further comprising selecting a second projection angle of the object with respect to a second two-dimensional projected image,
Wherein the two-dimensional projection image of is generated from the scan data during the step of scanning. 38. The method of claim 34, wherein successive image data slices are oscillating with respect to each other. 39. The method of claim 34, wherein the array of detectors is a two-dimensional array. 40. The method of claim 34, wherein the scan data is generated using a helical scan. 41. The method of claim 34, wherein the scan data is generated using a helical cone beam scan. 42. The method of claim 34, further comprising the step of reclassifying said scan data into parallel ray scan data. 43. The method of claim 34, wherein each image data slice has a tilt angle between the region and a longitudinal axis of the region and a transverse axis of the region intersecting the longitudinal axis. A slice plane having a normal axis that forms a rotation angle between the image data slices and the normal axis of successive image data slices having the same tilt angle and different rotation angles. . 44. An apparatus for generating a two-dimensional projected image of an object in a region having a longitudinal axis, the device comprising a source of radiation and an opposite side of the region. An array of detectors located thereon, wherein the source of radiation is capable of rotating about the longitudinal axis of the region while directing radiation toward the array of detectors. Mounted above, the array of detectors receives radiation from the region to generate scan data for the region; the method further comprises: a plurality of radiation along the longitudinal axis of the region. Means for defining a plurality of image data slices corresponding to the positions of the image data slices, wherein successive image data slices are not parallel to one another, Defining a plurality of scan data projections obtained from each of the plurality of view angles, each scan data projection including scan data at its respective view angle, the apparatus further comprising: Means for selecting one projection angle for the projected images of the image data; and means for identifying, for each of the image data slices, the view angle corresponding to the selected projection angle; Means for selecting, for each of the image data slices, a projection of the scan data corresponding to the identified view angle; and Means for generating a three-dimensional projection image. 45. The apparatus according to claim 44, wherein said array of detectors is also mounted on said rotatable member. 46. The apparatus according to claim 44, wherein the source of radiation is rotated about the longitudinal axis of the region while along the longitudinal axis of the region. Apparatus further comprising means for moving said object relative to a source of radiation and said array of detectors. 47. The apparatus according to claim 44, further comprising means for selecting a second projection angle for a second two-dimensional projected image of the object, wherein the means for generating comprises: An apparatus adapted to generate the second two-dimensional projected image from the scan data. 48. The apparatus according to claim 47, wherein the source of radiation is a cone beam source. 49. The apparatus according to claim 47, wherein the array of detectors is a two-dimensional array. 50. The apparatus according to claim 47, further comprising means for reclassifying the scan data into parallel ray scan data.