DE102009011801A1 - Method for generating a CT image data set with a specific X-ray energy spectrum and CT system - Google Patents

Abstract

The invention relates to a method for generating a CT image data set with a specific X-ray energy spectrum (S (E)) and a CT system (1) with program code (Prg-Prg) for this method. According to the invention, material distributions and local measurement spectrum-independent but energy-dependent attenuation functions $ I2 are estimated from the measured local weighted attenuation coefficients, preferably iteratively calculated by calculating the local energy weights $ I3, and then a CT image data set based on a predetermined energy spectrum (w (E)) and the calculated local measurement spectrum independent but energy dependent attenuation functions $ I4 are calculated and output.

Description

The The invention relates to a method for generating a CT image data set with a specific X-ray energy spectrum and a CT system with program code for this procedure, using a CT scan an object to be examined with the aid of at least one radiation source with a known radiation spectrum and at least one detector performed with a known spectral sensitivity and at least one projection data set from this CT scan is generated and from this at least a first CT image data set reconstructed by inverse radon or inverse transformation so that this at least one CT image data set a variety of image values, the local mean attenuation values of the examination object.

It is well known that due to different spectral weighting, ie the product of spectrum used and spectral detector sensitivity, of different radiator detector systems in a CT scan the measured and reconstructed attenuation data identical objects fail differently. Furthermore the known hardening of the radiation generates itself changing impression and artifacts in the reconstructed CT image. This creates the problem that a comparison of two CT examinations on different devices with different Spectral weights is difficult.

task The invention will now be to produce CT image data sets, on the one hand have no Strahlaufhärtungseffekte, on the other hand, the attenuation coefficients over the entire image represent an arbitrarily selected spectrum.

These The object is achieved by the features of the independent claims solved. Advantageous developments of the invention are Subject of subordinate claims.

The inventors have recognized the following:
Computed tomography is routinely performed to obtain three-dimensional images of the human body. The measured CT values describe a weighted attenuation coefficient of the X-radiation. Their spectral weighting is influenced by the X-ray spectrum of the X-ray tube used, the spectral detector properties and the attenuation object. Accordingly, the CT numbers usually have no quantitative properties.

The quantitative actual property of the scanned object is the spectral mass-dependent attenuation function. This is not direct in conventional CT devices measurable, since the projection data no energy resolution include. During the last decades energy-dissolving CT systems developed, such as dual-energy CT, dual-source CT or prototypes of a photon-counting CT device. In conjunction with spectral CT algorithms, such as the base material decomposition, is it possible to have a parametric representation of the spectral To obtain mass attenuation functions. The resulting Information is quantitative absolute values. In the practical Application are common to image data based formulations. They are of the above mentioned system sizes and affects the object's weakening.

The here described local spectral reconstruction (LSR) based on the description of the spectral weighting in the image plane of the CT system. The local weighting function (LWF) describes the Weighting of the spectral attenuation coefficients of the measured CT data. According to the invention Local weighting function used to perform various energy calibrations perform measured and simulated CT data, ie image data based on any virtual measurement spectra display. This also includes beam hardening corrections, Energy calibrations on different target energy spectra and Attenuation corrections for SPECT (= single photon Emission Computed Tomography, = single-photon emission computer tomography) or PET (= positron emission tomography).

• – CT-Scan eines Untersuchungsobjektes mit Hilfe mindestens einer Strahlungsquelle und mindestens eines Detektors und Erzeugung mindestens eines zu Rekonstruktionszwecken geeigneten Projektionsdatensatzes auf der Basis mindestens eines Röntgenenergiespektrums,
• – Rekonstruktion mindestens eines CT-Bilddatensatzes aus dem mindestens einen Projektionsdatensatz, wobei der CT-Bilddatensatz eine Vielzahl von Bildwerten aufweist, die lokale mittlere Schwächungswerte μ(r →) des Untersuchungsobjektes wiedergeben,
• – Ermittlung einer zum Scan jeweils verwendeten Spektralwichtung w(E), definiert als normierte Produktfunktion aus der energieabhängigen Wichtung des verwendeten Strahlungsspektrums S(E) und der spektralen Empfindlichkeit eines verwendeten Detektors D(E),
• – Bestimmung einer Verteilung vordefinierter Materialien im Untersuchungsobjekt auf der Basis der zuvor ermittelten lokalen mittleren Schwächungswerte μ(r →),
• – Bestimmung lokaler energieabhängiger Schwächungsfunktionen μ(E, r →) im Untersuchungsobjekt auf der Basis der zuvor ermittelten Materialverteilung,
• – Erstellung eines neuen tomographischen Bilddatensatzes durch Berechnung neuer örtlicher Schwächungswerte μ c(r →) je weils auf der Basis einer neuen vorbestimmten Spektralwichtung w_c(E) und der lokalen energieabhängigen Schwächungsfunktionen μ(E, r →).

In accordance with this knowledge described above, the inventors propose a method for CT scanning and reconstruction of an examination subject with a first X-ray energy spectrum and presentation of the examination subject corresponding to a CT scan with a second, virtual X-ray energy spectrum, with the following method steps:

• CT scan of an examination object with the aid of at least one radiation source and at least one detector and production of at least one projection data set suitable for reconstruction on the basis of at least one X-ray energy spectrum,
• Reconstruction of at least one CT image data set from the at least one projection data set, wherein the CT image data set has a plurality of image values, the local mean attenuation values μ (r →) of the object to be examined,
• Determination of a spectral weighting w (E) used for the scan, defined as a normalized product function from the energy-dependent weighting of the radiation spectrum S (E) used and the spectral sensitivity of a detector D (E) used,
• Determination of a distribution of predefined materials in the examination object on the basis of the previously determined local mean attenuation values μ (r →) .
• - Determination of local energy-dependent attenuation functions μ (E, r →) in the examination object on the basis of the previously determined material distribution,
• - Creation of a new tomographic image data set by calculation of new local attenuation values μ c (r →) depending Weil on the basis of a new predetermined spectral weighting w _c (E) and the local energy-dependent attenuation functions μ (E, r →) ,

It It should be noted that the variables given here are only for clarity and easier readability, with the described subject exclusively to the contents and meaning of the terms used.

This previously described method now allows on the basis Any CT scans with any X-ray spectra used and spectral detector sensitivities CT image data sets on the one hand no Strahlaufhärtungseffekte on the other hand, over the entire picture the middle Attenuation coefficients of any selected Represent X-ray spectrum.

Advantageously, the method described above can be improved if, in addition to the determination of local energy-dependent attenuation functions μ (E, r →) a calculation of local energy-dependent weighting functions Ω (E, r →) as a function of local mean attenuation values μ (r →) , the previously determined local energy-dependent attenuation functions μ (E, r →) and the spectral weighting w (E) used, and these local weighting functions Ω (E, r →) for the iteratively improving determination of the local energy-dependent attenuation functions μ (E, r →) is used until a predetermined iteration limit is reached.

By This iterative implementation of the method is thus at every iteration an improved determination of material distribution carried out, from each of which an improved new tomographic Image data set follows.

In addition, when creating the new tomographic image data set, it is now possible to calculate new local attenuation values μ c (r →) each based on a new predetermined spectral weighting w _c (E) and the local energy-dependent attenuation functions μ (E, r →) also a local weighting function dependent on the new spectral weighting w _c (E) Ω c (E, r →) be taken into account. Herewith a beam hardening is simulated.

verwendet werden, mit:

wobei P dem Vorwärtsprojektionsoperator bei einer Rekonstruktion eines CT-Bilddatensatzes und R^–1 inverse Radontransformationsoperator bei einer Rekonstruktion eines CT-Bilddatensatzes entsprechen.In concrete terms, this method can be used to calculate the measurement spectrum-dependent local weighting functions Ω (E, r →) in the places r → of the object under investigation the relationship

to be used with:

where P corresponds to the forward projection operator in a reconstruction of a CT image data set and R ^-1 inverse radon transformation operator in a reconstruction of a CT image data set.

Farther can the material distribution in the examination object over a threshold definition of mean minimum and maximum Attenuation values are determined.

Cheap for the suppression of noise effects it is also when determining the material distribution in the examination object at least one spatial filter is used.

Next the use of a new arbitrary spectral weighting for the calculation a new CT image dataset corresponding to a broader Radiation spectrum can also be a monoenergetic spectral weighting be used. Here, for example, the energy of 511 keV used, so the determined CT image data set for Strahlaufhärtungskorrektur be used in PET and / or SPECT examinations.

The The method described above can according to the invention on the one hand on a CT system, which has a control and processing unit with a memory for computer program code carried out On the other hand, it is also within the scope of the invention scan data already determined on a CT system or already reconstructed CT data sets on a separate computing system to transfer and there the method described above without sampling or without initial reconstruction.

In the following the invention including its application will be described in more detail with the aid of the figures, wherein only the features necessary for understanding the invention are shown. The following reference numerals and abbreviations are used: 1 : CT system; 2 : first X-ray tube; 3 : first detector; 4 : second x-ray tube (optional); 5 : second detector (optional); 6 : Gantry housing; 6.1 : Swivel arm; 7 : Examination object / patient / phantom; 8th : Examination couch; 9 : System axis; 10 : Control and processing unit with optional additional ECG function; 11 : Contrast agent applicator; 12 : ECG lead; 13 : C-arm system; A: weakening; D: detector; D (E): spectral detector sensitivity; E: energy; I, I ₀ : intensity; L: any path on which X-ray radiation is absorbed; l _{θ, t} : path to the projection angle θ and detector channel t; O: object; Prg ₁ prg _n : computer programs; S: X-ray source; S (E): X-ray energy spectrum; S ₁ -S ₇ : process steps; U: tube voltage; t: channel spacing; μ (r →) : mean attenuation coefficient; μ (E, r →) : spectral attenuation function; w (E): weighting function; ρ: density; θ: projection angle; Z: mass number.

It show in detail:

1 : Schematic representation of the attenuation measurement of a radiation;

2 : Calculated X-ray energy spectra S ₁ (E) and S ₂ (E) of a tungsten anode at acceleration voltages of U ₁ = 80 kVp and U2 = 140 kVp;

3 : Energy dependence of specific mass attenuation coefficients (μ / ρ) (E) of various specified materials;

4 : Path of the spectral detector sensitivity D (E) over the energy of a detector with 1.4 mm thick Gd ₂ O ₂ S scintillator;

5 : Course of the normalized energy-dependent weighting functions w ₁ (E) and w ₂ (E) of a radiator-detector system with the spectra 2 with the spectral detector sensitivity 4 about the energy;

6 : Representation of a phantom with actual attenuation values and a CT representation of this phantom with beam hardening artifacts;

7 : Schematic representation of a parallel projection geometry of a CT;

8th : Flowchart of the LSR method according to the invention;

9 : CT system for carrying out the method according to the invention;

10 : C-arm system for carrying out the method according to the invention.

In computed tomography, the spatial distribution of Hounsfield numbers H (r →) measured. They correspond to a weighted attenuation coefficient μ (r →) , In physical reality, the actual value of the attenuation coefficient of the scanned object, for example a patient, corresponds to the energy-dependent attenuation function μ (E, r →) , The measurement corresponds to a weighting of the physical reality of the actual attenuation function μ (E, r →) to the mean attenuation coefficient μ (r →) ,

The Spectral weighting is on the one hand by the measuring system used and on the other hand determined by the scanned object.

The The X-ray tube has a major influence on the measuring system and the detector.

The tube-dependent X-ray spectrum S (E) determines the energy distribution of the incident X-rays, These follow, for example, the typical tungsten emission properties. The spectral sensitivity of the detector D (E) describes the relative contribution of energy E. The normalized product from the tube spectrum and the detector response function w (E) gives the system weighting function (SWF). For small objects she approaches the local energy weighting. Typical diameter of scanned Patients or objects are usually a few tens of centimeters. In this case, the self-absorption of the object shifts the local energy weighting towards higher energies.

This so-called beam hardening effect is used in CT imaging routinely compensated. Usually for that The method used calculates the effective damping length in water and bone for each projection and compensated the associated shift of the X-ray spectrum to a medium energy value. The calculation with additional Existing contrast agent, such as iodine, is also possible. The algorithms reduce the normal beam hardening artifacts, like the bowl-shaped artifacts in cross-sectional photographs a patient or funnel-shaped artifacts nearby and between bones. Use conventional CT systems Algorithms based on these principles.

A quantitative application of the beam hardening corrections will be made in CH Yan, RT Whalen, GS Beaupre, SY Yen, and S. Napel, "Reconstruction Algorithm for Polychromatic CT Imaging: Application to Beam Hardening Correction", IEEE Trans. Med. Im., Vol. 19, no. 1, pp. 1-11, 2000 , described. In this document an iterative method with a linearized polychromatic forward projection is described. This gives the attenuation coefficient μ (r →) as a function weighted with the SWF from an image data set. It is also shown that dual-energy CT image data sets in particular for improving the precision of weighted attenuation coefficients μ (r →) can be used.

Here, a quantitative image-based spectral reconstruction method for CT applications is described. This application is hereafter called "local spectral reconstruction" (LSR). The central element is the local weighting function Ω (E, r →) , The local weighting function serves as a weighting function in the spectral integration of the actual local attenuation functions μ (E, r →) to the measured mean local attenuation coefficients μ (r →) CT image data records.

Consequently On the one hand, shifts in energy weighting can occur expressed and depending on the local weighting function be determined. On the other hand, based on the image data Link between the actual local energy-dependent attenuation functions and the measured image data a consistent description of many spectral Applications in CT, such as beam hardening corrections, Energy calibrations of the CT system, attenuation corrections for SPECT and PET, as well as the image-based basic material decomposition or the division into density and atomic number.

The 1 shows a schematic representation of the measuring arrangement of the X-radiation in a CT. The source S emits an X-ray quantum flux onto an object O. The object O consists of radiation-weakening material. The weakening is due to the energy-dependent weakening function μ (E, r →) locally r → described. The detector D registers the X-radiation exiting after the object O. Two independent measurements are performed, once with the object and once without the object. From the measured intensities I and I ₀ is the attenuation A = I / I ₀ ε [0 results; 1]. It describes the relative decreases in intensity due to the attenuation of the X-radiation as it passes through the object.

The spectral properties of the source, the object and the detector can be briefly described as follows: The X-ray source S emits X-radiation or X-ray quanta with the energy spectrum S (E). The physical unit for this is "quantum per energy", for example the number of quanta per energy in keV. The maximum of the emitted energy E is limited by the acceleration voltage of the X-ray tube. The 2 shows two typical X-ray spectra for the tube voltages U ₁ = 80 kVp and U ₂ = 140 kVp. The spectrum S (E) depends on the design of the X-ray tube and on other parameters such as anode angle, anode material and pre-filters. There are several models for measuring and calculating S (E) for different X-ray tubes. By way of example, reference is made to: DM Tucker, GT Barnes, and DP Chakraborty, "Semiempirical model for generating tungsten target x-ray spectra, "Medical Physics, vol. 18, no. 2, pp. 211-218, 1991 , and Birch and M. Marshall, "Computation of Bremsstrahlung X-ray Spectra and Comparison with Spectra Measured with Ge (Li) Detector," Physics in Medicine and Biology, vol. 24, no. 3, pp. 505-517, 1979 ,

The object O is determined by the spatial distribution of the spectral attenuation functions μ (E, r →) described. These can be determined by the density ρ and the mass attenuation function ( μ ρ ) (E, Z) be split: μ (E) = ρ ( μ ρ ) (E, Z). Eq. (1)

The mass attenuation function ( μ ρ ) (E, Z) is a characteristic function for a chemical element with the mass number Z. The 3 shows several exemplary selected weakening functions, including for the elements hydrogen (Z = 1), carbon (Z = 6), nitrogen (Z = 7) and oxygen (Z = 8).

mit der Teildichte ρ_i des i-ten Elements in g/cm³ und der dazugehörigen Massenzahl Z_i Die Schwächung der Röntgenstrahlung durch beliebige Objekte kann basierend auf der chemischen stöchiometrischen Zusammensetzung der Elemente beschrieben werden. Zum Beispiel kann der Photonenwirkungsquerschnitt von Wasser (H₂O) geschrieben werden als:

Matter of different materials can be described as a superposition of the elementary mass weakening functions. From this one obtains:

with the partial density ρ _{i of} the ith element in g / cm ³ and the associated mass number Z _i The attenuation of the X-ray radiation by arbitrary objects can be described on the basis of the chemical stoichiometric composition of the elements. For example, the photon action cross section of water (H ₂ O) can be written as:

ICRU Report 46 summarizes the chemical composition and photon cross-sections of biological tissue. The 3 shows the mass weakening function of femurs.

The detector D is described by the detector response function D (E). It contains the relative magnitude of the signal corresponding to the energy E. For an ideal integrating detector, the relationship D (E) = E can be assumed. In practice, however, D (E) has a complicated shape. The detector response function D (E) must be calculated or measured for a detailed description. Such a method is exemplified in the document S. Wirth, W. Metzger, K. Pham-Gia, and BJ Heismann, "Impact of Photon Transport Properties on the Detection Efficiency of Scintillator Arrays," IEEE Nuclear Science Symposium Conference, no. M11-212, pp. 2602-2603, 2003 , described. A typical detector response function D (E) of a Gd ₂ O ₂ S scintillator detector shows the 4 ,

mit dem Projektionspfad L. Die Gleichung (4) kann umgeschrieben werden in

mit der Definition der Systemgewichtungsfunktion (SWF)

With this parameterization of the source, the object and the detector, the measurement process can now be described. The measured attenuation A results from the two measured intensities I and I ₀ as:

with the projection path L. The equation (4) can be rewritten in

with the definition of the system weighting function (SWF)

The SWF can be calculated from the parameterization of S (E) and D (E) or obtained from transmission measurements. See for example EY Sidky, L. Yu, X. Pan, Y. Zou, and M. Vannier, "A robust method of x-ray source spectrum estimation from transmission measurements: Demonstrated on computer simulated, scatter free transmission data," Journal of Applied Physics , vol. 97, no. 124701, 2005 ,

The 5 Figure 2 shows two SWFs for a typical dual kVp scan of a CT system with the parameters for the x-ray tube and detector from the 2 and 4 ,

For monoenergetic radiation of energy E = E ₀ w (E) = δ (E - E ₀ ) and equation (5) is simplified

This corresponds to a radon transformation, as in J. Radon "On the Determination of Functions by their Integral Values along Certain Manifolds", Ber. Verh. Sachs. Akad. Leipzig, vol. 69, pp. 262-277, 1917 , is described.

Equation (5) and simplification for the monoenergetic case in equation (7) illustrate the fundamental dilemma of standard imaging in single-energy CT scans. The physical condition of the scanned object with respect to the interaction with the radiation is determined by the spectral mass attenuation functions μ (E, r →) completely defined. The measuring process is correctly described by the equation (5). Nevertheless, the corresponding data for μ (E, r →) can not be reconstructed from the standard CT measurements. Spectrally resolved sinogram data sets A _i (E) would be necessary to obtain the spectral coordinates of μ (E, r →) completely reconstruct. But even if these datasets were available, quantum noise would become a very limited description of μ (E, r →) to lead. Therefore, equation (5) already correctly describes the experimental data, even if the mass attenuation function μ (E, r →) can not be won because of lack of information.

In single-energy CT systems, this dilemma leads to an approximation. The radon transformation and its inversion are based on a linear X-ray physics according to Equation (7) to μ (r →) images to reconstruct. The errors generated by this assumption are commonly referred to as beam hardening artifacts. The underlying model assumes that equation (7) can be used approximately to determine the local mean mass attenuation coefficients. It is assumed that the X-ray quanta that penetrate through the object have an effective energy <E>. When the quanta pass through thick areas or areas of large mass number, such as bone, of the object, the effective energy <E> increases by a few keV according to the characteristics of the specific attenuation functions μ (E), since lower energy photons tend to absorb more are called higher energy photons, as in the 3 is shown. The X-ray spectrum is thus hardened. It follows that the reconstructed coefficients μ (r →) be underestimated with increasing beam hardening.

mitThe error of the estimation can be derived analytically, so that equation (5) can be rewritten

With

The first term of R usually leads to an overestimation of A and a consequent sub-determination of μ (r →) in the reconstructed picture. The 6 shows a schematic example from the medi Zinc CT.

Beam hardening corrections can reduce most of these artifacts in the practical application of CT systems. Assuming that R is small with respect to the object's attenuation or beam hardening correction, the essential result is that the weighted attenuation coefficients μ (r →) a CT image and the local mass attenuation functions μ (E, r →) connected via the following function:

This is a local relationship in every location r → from the CT dataset. It allows us to measure and reconstruct data μ (r →) to connect with the underlying physical reality, namely the local mass weakening function. Equation (10) highlights an important fact of imaging in single-energy CTs. The reconstructed attenuation coefficients μ (r →) and likewise the water-normalized CT numbers depend on the SWF w (E). If the properties S (E) of the X-ray tube are changed or if another detector response function D (E) is used, the reconstructed data changes. The relative contrast of the pictures changes. This means that the CT numbers are usually not comparable for different CT systems. By definition, the CT numbers obtained from single-energy CT measurements are not quantitative.

mit dem Vorwärtsprojektionsoperator P{.} und der Abkürzung der räumlichen Pfadintegration

mit dem Linienparameter α für die Pfadintegration.The 7 shows a standard projection geometry in a CT system. In parallel projection geometry, a ray is described by the projection angle θ and its channel distance t to the center of the CT detector. From this follows the typical projection formula

with the forward projection operator P {.} and the abbreviation of the spatial path integration

with the line parameter α for the path integration.

The reconstructed local mean attenuation coefficient is displayed as μ (r →) = R -1 {P {μ (E, r →)}} (13) with the inverse radon transformation operator R ^-1 {.}.

in die Gleichung (13) und unter Berücksichtigung der Bedingung, dass P{μ(E, r →)} unabhängig von E ist, erhält man die Gleichung

By inserting a factor 1 =

in the equation (13) and taking into account the condition that P {μ (E, r →)} is independent of E, one obtains the equation

führt zuThe expansion of equation (14) by the factor

leads to

mit der lokalen Wichtungsfunktion

This expression can be transformed into

with the local weighting function

Equation (15) thus combines the spectral attenuation function μ (E, r →) with the measured, weighted attenuation coefficient μ (r →) , This is followed by an image data based description of the measurement method in the CT and the reconstruction process.

The local weighting function Ω (E, r →) from equation (17) describes the effective spectral weighting at any object position. It depends on the spectral attenuation function of the scanned object μ (E, r →) , the image data reconstruction process R ^-1 {.} and the measurement process described by the operator P {.}. The weighting function w (E) results from the weighting function of the system in equation (6).

In the practical application of CT only weighted attenuation coefficients μ (r →) measured. To calculate the local weighting function, an estimate of the spectral attenuation functions is made μ (E, r →) depending on the input data needed. A dual energy scan results in two attenuation data sets μ 1 (r →) and μ 2 (r →) , The base material decomposition is applied in an image data set based form to parameterize μ (E, r →) to obtain. This approach is described by

wobei die Elemente der Matrix K ausgedrückt werden durch

This term separates the energy-dependent basis function f _j (E) from the location-dependent coefficients c j (r →) , The typical values of the basic function in the medical application of CT is a combination of the mass-dependent attenuation functions of water and bone. From equation (16) follows

wherein the elements of the matrix K are expressed by

Equation (19) is with the coefficients c j (r →) simply invertible by inverting the matrix K. However, also the circular dependencies need K → c j (r →) → μ (E, r →) Ω i (E, r →) → K be dissolved. This leads to a two-phase iterative method according to the flowchart in FIG 8th , Here, first in method step S _1, the initial local weighting function is estimated by Ω i (K = 0) (E, r →) = w (E) is set. For example, this may be the result of the knowledge of the initially present CT display with the measured and reconstructed average local attenuation coefficients μ (r →) be estimated in step S ₂ . From the two results of steps S1 and S2, a first estimate of the local mass attenuation functions is made μ (E, r →) in step S ₃ . This results in the calculation of the local weighting functions Ω (E, r →) in step S ₄ . In addition, from the knowledge of the local mass attenuation functions μ (E, r →) and a predetermined desired spectrum in step S ₇ in accordance with the invention, the local weighted attenuation coefficients of the object under consideration with respect to the arbitrary assumed spectrum are calculated and output as a CT representation. If the method for optimization is to be carried out iteratively, these steps can be repeated as often as desired according to the flow diagram shown after a decision in step S ₅ , wherein the last calculated local weighting function is output in step S ₆ . In this way, at every k th iteration step, the estimation of μ i (K) (E, r →) and Ω i (K) (E, r →) ,

This method is referred to herein as Local Spectral Reconstruction (LSR). It leads to an estimation of both the local weighting function and the attenuation functions μ (E, r →) , The LSR method can be transferred to multichannel spectral CT and base material decomposition, for example, with a number of N> 2 spectral channels and a number M <= N base materials. For the single-energy CT can μ (E, r →) from an energy-weighted effective attenuation coefficient μ (r →) be estimated.

From the LSR method according to equations (16) and (17)), an estimate of the local weighting function and the actual accuracy of the spectral attenuation functions is obtained μ (E, r →) of the object. The information from the local weighting function provides a deeper understanding of the energy weighting process in CT imaging. For the quantitative application of the spectral CT are the attenuation functions obtained from it μ (E, r →) the main result. The associated parameters such as basis material coefficients can be graphically displayed or analyzed for specific diagnostic questions.

It is important to note that the weakening function μ (E, r →) theoretically not affected by the weakening effects of the object, the properties of the reconstruction and the measurement method. For example, the core of the reconstruction of dual-energy measurements can be taken into account. This can improve the pixel registration between the records.

In practice, exact descriptions of the weighting function w (E) and the measurement operator P {.} Are necessary to ensure quantitative results. It should be noted that the reconstruction operator R ^-1 {.} Yields both the image reconstruction and the calculation of the local weighting function. That being said, there are no further effects on the accuracy and precision of μ (E, r →) ,

Basically, there are several different objectives of the inventive weighting set forth above:
It can be used for beam hardening corrections, for example, to obtain a constant system weighting (SWF) function of an image data set as described in US Pat 5 for w (E) CT measurement for 80 kVp and 140 kVp tube voltage is shown.

Furthermore, monoenergetic calibrations can be performed with a target weighting function given by w _c (E) = δ (E - E ₀ ). One application of these monoenergetic attenuation coefficients is the contrast enhancement in image differences of particular tissue.

Another application of this energy calibration is the attenuation correction in SPECT / CT and PET / CT. This results in monoenergetic attenuation coefficients of, for example, 141 keV and 511 keV for the corresponding tracer emission lines of Tc ^99m and F ¹⁸ glucose.

Furthermore can according to the invention an energy calibration be performed on any virtual spectrum.

ausgeführt. Dabei ist μ C(r →) der korrigierte Bilddatensatz für die durch das LSR-Verfahren bestimmten Schwächungsfunktionen μ(E, r →) und einer ausgewählte Zielenergiegewichtung w_c(E).For all applications, the energy calibration is according to the formula

executed. It is μ C (r →) the corrected image data set for the attenuation functions determined by the LSR method μ (E, r →) and a selected target energy weight w _c (E).

The 9 shows an exemplary CT system 1 with which the method according to the invention can be carried out. The CT system 1 shows a first tube / detector system with an x-ray tube 2 and an opposite detector 3 on. Optionally, this CT system 1 via a second x-ray tube 4 with an opposite detector 5 feature. Both tube / detector systems are located on a gantry in a gantry housing 6 is arranged and during the scan around a system axis 9 rotates. The patient 7 is located on a movable examination couch 8th that are either continuous or sequential along the system axis 9 through the gantry housing 6 is pushed measuring field, wherein the attenuation of the X-rays emitted by the X-ray tubes is measured by the detectors.

While the measurement can be patient 7 with the help of a contrast agent applicator 11 Also, a contrast agent bolus be injected so that blood vessels can be better recognized or a perfusion measurement can be performed. In cardio recordings may additionally, with the help of an ECG lead 12 , cardiac activity is measured and an ECG gated scan is performed.

The control of the CT system is carried out with the aid of a control and processing unit 10 , in which there are computer programs Prg ₁ to Prg _n , which also the above-described inventive method by being able to lead. In addition, via this control and processing unit 10 also the output of image data takes place.

at this CT system with two separate x-ray sources For example, an X-ray tube with an acceleration voltage of 80 kVp and the other x-ray tube with 140 kVp operated. This results in different measurements Spectral weightings, which - with the same spectral sensitivity the detectors used - from the different X-ray spectra of the two x-ray tubes come. Alternatively, however, it is also possible in both x-ray tubes the same radiation spectrum to use, but for different spectral Sensitivity of the detectors. Also a combination Both measures are possible.

The method according to the invention can also be used in conjunction with a C-arm system 1 be used as it is in the 10 is shown. The C-arm system shown here 13 also has an x-ray tube 2 with an opposing planar detector 3 , Both systems are using a swivel arm 6.1 which is attached to a housing 6 is attached, in any position around the patient 7 to pan and scan a measurement field. The patient 7 is on a patient bed 8th additionally using a contrast agent application system 11 to inject contrast media, if necessary, to visualize blood vessels. The system is controlled by a control and processing unit 10 , which has in its memory computer programs Prg ₁ to Prg _n , which can also perform, among other things, the inventive method for image processing. Measurements with different spectral weights can be realized, for example, by the use of an energy-specific detector system.

Both previously described systems are suitable for carrying out of the method according to the invention, the bases thereof previously described.

All in all Thus, the invention provides a method for generating a CT image data set with a specific X-ray energy spectrum and describe a CT system with program code for this method, according to the invention from the measured local weighted coefficients of attenuation material distributions and from this local measurement spectrum independent but energy dependent Attenuation functions estimated, preferably iteratively via a calculation of local energy weights recalculated, and then a CT image data set the basis of a predetermined energy spectrum and the calculated local non-spectra independent but energy dependent Attenuation functions and calculated as a CT image representation be issued.

It it is understood that the above features of the invention not only in the specified combination, but also in other combinations or alone, without to leave the scope of the invention.

1

CT system

2

first X-ray tube

3

first detector

4

second X-ray tube (optional)

5

second Detector (optional)

6

gantry

6.1

swivel arm

7

Examination subject / patient / Phantom

8th

examination table

9

system axis

10

Tax- and arithmetic unit with optional additional ECG function

11

Kontrastmittelapplikator

12

ECG lead

13

C-arm system

A

attenuation

D

detector

D (E)

spectral detector sensitivity

e

energy

I, I ₀

intensity

L

one any path on which X-rays are absorbed

l _{θ, t}

path to the projection angle θ and detector channel t

O

object

Prg ₁ prr _n

computer programs

S

X-ray source

S (E)

X-ray energy spectrum

S ₁ -S ₇

steps

U

tube voltage

t

channel spacing

μ (r →)

middle attenuation coefficient

μ (E, r →)

spectral attenuation function

w (E)

Weighting function

ρ

density projection angle

Z

mass number

QUOTES INCLUDE IN THE DESCRIPTION

This list The documents listed by the applicant have been automated generated and is solely for better information recorded by the reader. The list is not part of the German Patent or utility model application. The DPMA takes over no liability for any errors or omissions.

Cited non-patent literature

• CH Yan, RT Whalen, GS Beaupre, SY Yen, and S. Napel, "Reconstruction Algorithm for Polychromatic CT Imaging: Application to Beam Hardening Correction", IEEETrans. Med. Im., Vol. 19, no. 1, pp. 1-11, 2000 [0036]
• - DM Tucker, GT Barnes, and DP Chakraborty, "Semiempirical model for generating tungsten target x-ray spectra," Medical Physics, vol. 18, no. 2, pp. 211-218, 1991 [0040]
• Birch and M. Marshall, "Computation of Bremsstrahlung X-ray Spectra and Comparison with Spectra Measured with Ge (Li) Detector," Physics in Medicine and Biology, vol. 24, no. 3, pp. 505-517, 1979 [0040]
• - S. Wirth, W. Metzger, K. Pham-Gia, and BJ Heismann, "Impact of Photon Transport Properties on the Detection Efficiency of Scintillator Arrays," IEEE Nuclear Science Symposium Conference, no. M11-212, pp. 2602-2603, 2003 [0045]
• - EY Sidky, L. Yu, X. Pan, Y. Zou, and M. Vannier, "A robust method of x-ray source spectrum estimation from transmission measurements: Demonstrated on computer simulated, scatter free transmission data," Journal of Applied Physics, vol. 97, no. 124701, 2005 [0047]
• - J. Radon "On the Determination of Functions by Their Integral Values along Certain Manifolds", Ber. Verh. Sachs. Akad. Leipzig, vol. 69, pp. 262-277, 1917 [0050]

Claims (9)

A method for CT scanning and reconstruction of an examination subject with at least a first X-ray energy spectrum and representation of the examination subject corresponding to a CT scan with a second, virtual X-ray energy spectrum, comprising the following method steps: 1.1. CT scan of an examination subject ( 7 ) with the aid of at least one radiation source ( 2 . 4 ) and at least one detector ( 3 . 5 ) and generating at least one projection data set suitable for reconstruction purposes on the basis of at least one X-ray energy spectrum, 1.2. Reconstructing at least one CT image data set from the at least one projection data set, wherein the CT image data set has a multiplicity of image values representing the local average attenuation values ( μ (r →)) of the examination object ( 7 ), 1.3. Determination of a spectral weighting (w (E)) used for the scan, defined as a normalized product function from the energy-dependent weighting of the radiation spectrum used (S (E)) and the spectral sensitivity of a detector used (D (E)), 1.4. Determination of a distribution of predefined materials in the examination subject ( 7 ) based on the previously determined local mean attenuation values ( μ (r →)) , 1.5. Determination of local energy-dependent attenuation functions (μ (E, r →)) in the examination object ( 7 ) on the basis of the previously determined material distribution, 1.6. Creation of a new tomographic image data set by calculation of new local attenuation values ( μ c (r →)) each based on a new predetermined spectral weighting (w _c (E)) and the local energy-dependent attenuation functions (μ (E, r →)) , Method according to the preceding patent claim 1, characterized in that 2.1. after determining local energy-dependent attenuation functions (μ (E, r →)) a calculation of local energy-dependent weighting functions (Ω (E, r →)) as a function of local mean attenuation values ( μ (r →)) , the previously determined local energy-dependent attenuation functions (μ (E, r →)) and the spectral weighting used (w (E)), and 2.2. these local weighting functions (Ω (E, r →)) for improved determination of the local energy-dependent attenuation functions (μ (E, r →)) as long as in an iteration of the method steps according to the features 1.4 to 1.5 are used until a predetermined iteration limit is reached. Method according to the preceding claim 2, characterized in that in the preparation of the new tomographic image data set by calculation of new local attenuation values ( μ c (r →)) each based on a new predetermined spectral weighting (w _c (E)) and the local energy-dependent attenuation functions (μ (E, r →)) also a local weighting function dependent on the new spectral weighting (w _c (E)) (Ω c (E, r →)) is being used. Method according to one of the preceding claims 2 to 3, characterized in that for calculating the local measurement spectrum-dependent weighting functions (Ω (E, r →)) in the places (r →) of the examination object ( 7 ) the relationship

is used with:

where P corresponds to the forward projection operator in a reconstruction of a CT image data set and R ^-1 Radon transform operator in a reconstruction of a CT image data set. Method according to one of the preceding claims 1 to 4, characterized in that the material distribution in the examination object ( 7 ) is determined via a threshold definition of mean minimum and maximum attenuation values. Method according to one of the preceding claims 1 to 5, characterized in that in the determination of the material distribution in the examination object ( 7 ) at least one spatial filter is used to suppress noise effects. Method according to one of the preceding claims 1 to 6, characterized in that as a new spectral weighting (w _c (E)) a monoenergetic spectral weighting is used. Method according to the preceding Claim 7, characterized in that the monoenergetic Spectral weighting takes place at an energy of 511 keV and the thus determined CT image data set for Strahlaufhärtungskorrektur used in PET and / or SPECT CT examinations CT system for scanning an examination subject comprising a control and computing unit ( 10 ) with a memory for computer program code (Prg ₁ -Prg _n ), characterized in that computer program code (Prg ₁ -Prg _n ) is stored in the memory, which can perform the method steps of one of the preceding method claims in operation.