JP2014166200A - Magnetic resonance apparatus and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a magnetic resonance apparatus that improves accuracy in detecting a position of a liver edge.SOLUTION: A magnetic resonance apparatus converts a navigator signal into a profile Fn in a real space. The apparatus uses a window to apply filter processing to the profile Fn. The apparatus sets a first search area W1 to a profile Fn' obtained by the filter processing and uses a threshold T1 to detects a temporary position Et1 of a liver edge from the first search area W1. Then, the apparatus sets a second search area W2 on the basis of the temporary position Et1 and uses a threshold T2 to detect a position Et2 of the liver edge corresponding to an actual position of the liver edge from the second search area W2.

Description

  The present invention relates to a magnetic resonance apparatus that collects navigator signals including position information of a predetermined part, and a program applied to the magnetic resonance apparatus.

  A slice tracking method is known in which a slice position is changed based on a respiratory signal of a subject (see Patent Document 1).

JP 2007-75387 A

  As one of the slice tracking methods, a TRON (Tracking Only Navigator) method is known. The TRON method corrects the position of the slice based on the position of the edge of the liver obtained by the navigator sequence. Then, an imaging sequence for acquiring image data according to the corrected slice position is executed. In the TRON method, the position of the slice is corrected based on the position of the edge of the liver, so that it is possible to reduce body movement artifacts. However, in the TRON method, the excitation region due to the imaging sequence overlaps with the excitation region due to the navigator sequence, so that the signal obtained by the navigator sequence deteriorates due to the spin saturation effect, and the detection accuracy of the position of the liver edge is deteriorated. is there. Therefore, it is desired to improve the detection accuracy of the position of the edge of the liver.

A first aspect of the present invention is a magnetic resonance apparatus that sets a slice at a predetermined part and acquires image data of the predetermined part,
A collecting means for collecting a navigator signal including position information of the predetermined part from a navigator region including at least a part of the predetermined part;
Conversion means for converting the navigator signal into a profile in real space;
Filter means for setting a window at each position of the profile and filtering the profile based on a signal value in the window, and setting a window width of the window based on a slice thickness of the slice Filter means;
The magnetic resonance apparatus includes detection means for detecting a position of the predetermined portion based on the filtered profile.

A second aspect of the present invention is a collecting means for collecting a navigator signal including positional information of the predetermined part from a navigator region including an edge of the predetermined part;
Conversion means for converting the navigator signal into a profile in real space;
A magnetic resonance apparatus having detection means for detecting a position of an edge of the predetermined part based on the profile,
The detection means includes
First edge position detecting means for obtaining a first threshold value of the signal value of the profile and detecting a temporary position of an edge of the predetermined portion based on the first threshold value;
Search range setting means for setting an edge search range of the predetermined part in the profile based on the provisional position of the edge;
A second edge position detecting means for obtaining a second threshold value of the signal value of the profile and detecting an edge position of the predetermined part from the search range based on the second threshold value; It is a magnetic resonance apparatus.

According to a third aspect of the present invention, a slice is set at a predetermined part, image data of the predetermined part is acquired, and positional information of the predetermined part is obtained from a navigator region including at least a part of the predetermined part. A magnetic resonance apparatus program for collecting navigator signals including:
A conversion process for converting the navigator signal into a profile in real space;
A filter process for setting a window having a window width determined based on a slice thickness of the slice at each position of the profile, and filtering the profile based on a signal value in the window;
This is a program for causing a computer to execute detection processing for detecting the position of the predetermined part based on the filtered profile.

A fourth aspect of the present invention is a program for a magnetic resonance apparatus that collects a navigator signal including position information of the predetermined part from a navigator area including an edge of the predetermined part.
A conversion process for converting the navigator signal into a profile in real space;
A program for causing a computer to execute detection processing for detecting a position of an edge of the predetermined part based on the profile;
The detection process includes
A first edge position detection process for obtaining a first threshold value of the signal value of the profile and detecting a temporary position of an edge of the predetermined part based on the first threshold value;
A search range setting process for setting a search range for the edge of the predetermined part in the profile based on the temporary position of the edge;
A second edge position detection process for obtaining a second threshold value of the signal value of the profile and detecting an edge position of the predetermined part from the search range based on the second threshold value. It is a program.

  The detection accuracy of the position of a predetermined part can be improved.

1 is a schematic view of a magnetic resonance apparatus according to a first embodiment of the present invention. It is a figure which shows roughly the imaging | photography site | part in a 1st form. It is explanatory drawing of the scan implemented with a 1st form. It is a figure which shows the flow of a 1st form. It is a figure which shows the image data acquired by localizer scan SC1. It is a figure which shows an example of the set slice and navigator area | region. It is a figure which shows the acquired respiratory signal schematically. It is a figure which shows an example of the set reference position. It is an illustration of a navigator sequence A _1. Profile F ₁ in the real space obtained by performing inverse Fourier transform on the navigator signals S ₁ is a diagram schematically showing. The position P ₁ of the detected edge is a diagram schematically showing. The navigator signal S ₂ collected by the navigator sequence A ₂ is a diagram schematically showing. The profile F ₂ in the real space obtained by performing inverse Fourier transform on the navigator signal S ₂ is a diagram schematically showing. Is an explanatory view of the last navigator is executed sequence A _n and imaging sequence B _n. It is explanatory drawing of the phenomenon in which the signal value of a profile falls. It is an explanatory view of a filtering profile F _n. And profile F _n before filtering, shows side by side the profile F _{n 'after} filtering. It is a figure which shows an example when the signal value in the vicinity position of the edge of a liver falls. It is a figure which shows schematically profile _Fn 'after a filter process. It is the schematic of MR apparatus of the 2nd form. It is a figure which shows an example of the 1st search range W1. It is explanatory drawing when detecting the temporary position of the edge of a liver from search range W1. It is a figure which shows an example of the 2nd search range W2. It is explanatory drawing when the position of the edge of a liver is detected from the search range W2. It is the schematic of the MR apparatus of the 3rd form. Is a diagram showing a profile F _n obtained by converting the navigator signal S _n. It is a figure which shows an example of the 1st search range W1. It is explanatory drawing when detecting the temporary position of the edge of a liver from search range W1. It is a figure which shows an example of the 2nd search range W2. It is explanatory drawing when the position of the edge of a liver is detected from the search range W2.

  Hereinafter, although the form for inventing is demonstrated, this invention is not limited to the following forms.

(1) First Embodiment FIG. 1 is a schematic view of a magnetic resonance apparatus according to a first embodiment of the present invention.
A magnetic resonance apparatus (hereinafter referred to as “MR apparatus”, MR: Magnetic Resonance) 100 includes a magnet 2, a table 3, a receiving coil 4, and the like.

  The magnet 2 has a bore 21 in which the subject 10 is accommodated. The magnet 2 includes a superconducting coil, a gradient coil, an RF coil, and the like.

  The table 3 has a cradle 3 a that supports the subject 10. The cradle 3a is configured to be able to move into the bore 21. The subject 10 is transported to the bore 21 by the cradle 3a.

  The reception coil 4 is attached to the subject 10. The receiving coil 4 receives a magnetic resonance signal from the subject 10.

  The MR apparatus 100 further includes a transmitter 5, a gradient magnetic field power source 6, a control unit 7, an operation unit 8, a display unit 9, and the like.

  The transmitter 5 supplies current to the RF coil, and the gradient magnetic field power source 6 supplies current to the gradient coil. A combination of the magnet 2, the receiving coil 4, the transmitter 5, and the gradient magnetic field power source 6 corresponds to the collecting means.

  The control unit 7 transmits necessary information to the display unit 9 and reconstructs an image based on data received from the receiving coil 4 so as to realize various operations of the MR device 100. Control the operation of each part. The control unit 7 includes conversion means 71 to detection means 73 and the like.

The conversion means 71 converts the navigator signal into a real space profile.
The filter unit 72 filters the profile obtained by the conversion unit 71.
The detection unit 73 detects the position of the edge of the liver based on the profile.

  The control unit 7 is an example of a unit that constitutes the conversion unit 71 to the detection unit 73, and functions as these units by executing a predetermined program.

The operation unit 8 is operated by an operator and inputs various information to the control unit 7. The display unit 9 displays various information.
The MR apparatus 100 is configured as described above.

FIG. 2 is a diagram schematically showing an imaging region in the first embodiment, and FIG. 3 is an explanatory diagram of a scan performed in the first embodiment.
In the first form, the imaging region is a region including the liver. In order to collect image data of the imaging region, a localizer scan SC1, a pre-scan SC2, and a main scan SC3 are executed.

The localizer scan SC1 is a scan for acquiring positioning image data used for positioning a slice.
The pre-scan SC2 is a scan executed to determine the reference position of the liver edge (lung side).

The main scan SC3 is a scan for acquiring liver image data. In this scanning SC3, the navigator sequence _A 1 to A _n and imaging sequence _B 1 .about.B _n is performed.

Navigator sequence A ₁ to A _n from crossing the boundary between the lung and liver navigator region R _{nav (see} FIG. 2), a sequence for collecting the navigator signal including position information of the liver.
The imaging sequences B _{1 to} B _n are sequences for acquiring image data of the imaging region.

Hereinafter, a flow when acquiring image data of an imaging region will be described.
FIG. 4 is a diagram showing a flow of the first embodiment.
In step ST1, localizer scan SC1 is executed (see FIG. 5).

FIG. 5 is a diagram showing image data acquired by the localizer scan SC1.
Positioning image data H used for positioning the slice is acquired by the localizer scan SC1. After obtaining the positioning image data H, the process proceeds to step ST2.

In step ST2, the operator sets the slice position, slice thickness, navigator area, and the like based on the positioning image data H. FIG. 6 shows an example of the set slice and navigator area. Slices SL _{1 to} SL _m are set so as to cover the entire liver. The navigator region R _nav is set so as to cross the boundary between the lung and the liver. After the slices SL _{1 to} SL _m and the navigator region R _nav are set, the process proceeds to step ST3.

In step ST3, pre-scan SC2 is executed. In the pre-scan SC2, the navigator sequence is repeatedly executed. The navigator sequence is a sequence for detecting the position of the edge of the liver in the SI direction in the navigator region R _nav . Since the position of the liver edge in the SI direction changes due to the respiratory motion of the subject, the respiratory signal of the subject can be acquired by repeatedly executing the navigator sequence. FIG. 7 schematically shows the acquired respiratory signal. After acquiring the respiratory signal, the process proceeds to step ST4.

In step ST4, the reference position in the SI direction of the edge of the liver is set based on the respiratory signal acquired in step ST3. FIG. 8 shows an example of the set reference position. In this embodiment, the position when the subject finishes exhaling is set as the reference position _{Pref in} the SI direction of the edge of the liver. When the subject exhales, the upper end of the liver moves to the S side, and when the subject inhales, the upper end of the liver moves to the I side. Therefore, by detecting the maximum value of the respiration signal, the position when the subject finishes exhaling can be detected. The positional relationship among the slices SL _{1 to} SL _m , the navigator region R _nav, and the reference position P _ref is schematically shown on the respiratory signal in FIG. The reference position P _ref may be set manually by the operator while viewing the respiratory signal, or may be automatically set based on the respiratory signal. After setting the reference position _{P ref,} the process proceeds to step ST5.

In step ST5, the main scan SC3 is executed.
In this scanning SC3, firstly, navigator sequence _{A 1} is executed (see FIG. 9).

Figure 9 is an illustration of a navigator sequence A _1.
By navigator sequence _{A 1} is performed, navigator signals _{S 1} from the navigator region _{R nav} is collected. After collecting the navigator signal S _1, converting means 71 (see FIG. 1), by inverse Fourier transform of the navigator signals S _1, determining the profile of the real space. FIG. 10 schematically shows a profile F ₁ in real space obtained by performing inverse Fourier transform on the navigator signal S ₁ . Profile _{F 1} represents the change in the signal value of the SI direction in the navigator region _{R nav.}

The liver side (I side) has a high signal value, but the lung side (S side) has a low signal value. Therefore, the position of the edge on the upper end side (lung side) of the liver can be detected by detecting the position where the signal value falls. Figure 11 shows the position P ₁ of the detected edges schematically. After detecting the position P ₁ of the edge, it calculates a difference [Delta] d ₁ between the reference position P _ref of the detection position P ₁ and the liver edge of the edge. After obtaining the difference [Delta] d _1, to correct the position of the slice _SL 1 to SL _m by the difference [Delta] d _1, according to the slice _SL 1 to SL _m after the correction, the imaging sequence _{B 1} is executed. In the imaging sequence _{B 1,} to excite the slice _SL 1 to SL _m after the correction in order to collect data for one line to several lines of k-space from each slice _SL 1 to SL _m.

After executing the imaging sequence B _1, then navigator sequence A ₂ is executed. Figure 12 shows the navigator signal S ₂ collected by the navigator sequence A ₂ schematically. After collecting the navigator signal S _2, and the inverse Fourier transform of the navigator signal S _2, obtaining the profile F ₂ in the real space. Figure 13 shows a profile F ₂ in the real space obtained by performing inverse Fourier transform on the navigator signal S ₂ schematically. After obtaining the profile F ₂ , the edge position P ₂ is detected, and a difference Δd ₂ between the edge detection position P ₂ and the reference position P _ref of the liver edge is obtained. After obtaining the difference [Delta] d _2, to correct the position of the slice _SL 1 to SL _m by the difference [Delta] d _2, according to the slice _SL 1 to SL _m after the correction, the imaging sequence _{B 2} is executed. In the imaging sequence _{B 2,} to excite the slice _SL 1 to SL _m after the correction in order to collect data for one line to several lines of k-space from each slice _SL 1 to SL _m.

  Similarly, after the edge position is detected by the navigator sequence, the slice position is corrected based on the difference between the edge detection position and the edge reference position, and the imaging sequence is executed.

In this way, the navigator sequence and the imaging sequence are executed alternately. Figure 14 is an explanatory view of the last navigator is executed sequence A _n and imaging sequence B _n. By navigator sequence _{A n} is run, the navigator region _{R nav} navigator signal _{S n} are collected. After collecting the navigator signal S _n, the inverse Fourier transform of the navigator signals S _n, obtains the profile F _n in the real space. After determining the profile _{F n,} detects the position _{P n} of the edge, calculates a difference [Delta] d _n between the reference position _{P ref} of the detection position _{P n} and liver edges of edge. After obtaining the difference [Delta] d _n, correcting the position of the slice _SL 1 to SL _m by the difference [Delta] d _n, according to the slice _SL 1 to SL _m after the correction, imaging sequence _{B n} is performed. In the imaging sequence B _n , the corrected slices SL _{1 to} SL _m are sequentially excited, and data for the remaining one line to several lines in the k space is collected from each of the slices SL _{1 to} SL _m .
In this way, the scan ends.

In this embodiment, to detect the position of the liver edge by navigator sequence A ₁ to A _n, because to correct the position of the slice on the basis of a difference between the detected position and the edge reference position of the edge, reducing artifacts such as ghosting It is possible to obtain processed image data.

However, since the imaging sequences B _{1 to} B _n have excitation pulses for exciting the slice, each time the imaging sequence is executed, the intersection between the navigator region R _nav and the slice is excited. Therefore, the excitation pulses of the imaging sequences B _{1 to} B _n affect the navigator signal, and a phenomenon that the signal value of the profile decreases at a position away from the edge of the liver may occur (see FIG. 15).

FIG. 15 is an explanatory diagram of a phenomenon in which the signal value of the profile decreases.
In the following, for convenience of explanation, by taking the signal values of the profile F _n, the signal value of the profile will be described phenomenon to decrease, also lowering of the signal values of other profiles can be explained similarly.

As described above, since the intersection between the navigator region R _nav and the slice is excited by the excitation pulse of the imaging sequence, the navigator signal _Sn is deteriorated by the influence of the excitation pulse. Therefore, when the navigator signal S _n is converted into a real space profile F _n , a region R in which the signal value decreases may appear in the profile F _n . As a result, in a different position from the actual position P _e of the liver edge, it will appear the falling E _d of the signal values, which may result in erroneous detection of the position of the liver edge. Therefore, in the present embodiment, the profile F _n is filtered so that the edge of the liver is not erroneously detected even if the signal value decreases. Hereinafter, a filtering method will be described.

Figure 16 is an explanatory diagram of a filtering profile F _n.
Filter means 72 (see FIG. 1) is the profile F _n, to position a window for filtering.

FIG. 16A shows the initial position of the window W. FIG.
Filter means 72, based on the position P = P 1 _(liver side position) of the SI direction profile F _n pixels, sets the initial position of the window W. Here, the left edge of the window W is to match the position P ₁ of the pixel positions the window W.

  The window width x of the window W is set wider than the width d of the region R where the signal value decreases. Since the width d is substantially equal to the slice thickness, the window width x is set wider than the slice thickness (for example, twice the slice thickness).

After positioning the window W, the filter means 72 searches the signal values of the pixel positions P _{1 to} P _i in the window W and detects the maximum value of the signal. Here, the signal value S _i of the pixel P _i is the maximum value. Thus, the filter means 72 detects a signal value _{S i} of the pixel _{P i} as the maximum value. After detecting the maximum value S _{i of the} signal, the filter means 72 replaces the signal value S ₁ at the pixel position P ₁ with the maximum value S _i of the detected signal. FIG. 16E (right side of FIG. 16) shows a state where the signal value at the position P ₁ in the SI direction of the pixel is replaced with “S _i ”. After replacing the signal value, the filter means 72 moves the window W to the right (lung side) by one pixel (see FIG. 16B).

FIG. 16B is a diagram illustrating a state after the window W is moved to the right side (lung side) by one pixel.
The filter means 72 moves the position of the window W to the lung side by 1 pixel. Thus, the window W includes signal values of positions P = P _{2 to} P _{i + 1} in the SI direction of the pixels. The filter means 72 searches the signal values at the pixel positions P _{2 to} P _{i + 1} in the window W, and detects the maximum value of the signal values. Here, the signal value _{S i + 1} of the pixel _{P i + 1} is the maximum value. Thus, the filter means 72 detects a signal value _{S i + 1} of the pixel _{P i + 1} as the maximum value. After detecting the maximum value S _{i + 1} of the signal, the filter means 72 replaces the signal value S ₂ at the pixel position P ₂ with the maximum value S _{i + 1} of the detected signal. FIG. 16E shows a state where the signal value at the position P ₂ in the SI direction of the pixel is replaced with “S _{i + 1} ”.

Similarly, the filter unit 72 moves the window W to the right (lung side) by one pixel, and each time the window W is moved, the maximum value of the signal value is detected from within the window W and the pixel in the SI direction is detected. The signal value at position P is replaced with the maximum value of the detected signal. For example, in FIG. 16 (c) shows a state when the window W is moved to the position P = P _j of SI direction of pixels. In FIG. 16C, the maximum value S _{k of the} signal is detected from the window W. Therefore, the filter means 72 replaces the signal value at the position P _{j in} the SI direction of the pixel with “S _k ”.

Finally, the filter means 72 moves the window W to the position P = _Pz in the SI direction of the pixel. FIG. 16D shows a state when the window W is moved to a position P = _Pz in the SI direction of the pixel. In FIG. 16 (d), the the window W, and includes only the signal _{S z} position P = _{P z.} In this case, since only the signal S _z is detected from the window W, the signal value at the position P _z remains “S _z ”.

In this way, the profile F _n is filtered. FIG. 17 shows the profile F _n before filtering and the profile F _n ′ after filtering. The signal value falling edge _Ed appears in the profile F _n before the filtering process. However, since the signal value in the low signal region R is replaced with the maximum value of the signal in the window W by performing the filtering process, the falling edge _Ed of the signal value due to the low signal region R can be eliminated. Therefore, by detecting the position of the liver edge from the filtered profile F _n ′, the detection error of the liver edge position can be reduced.

  In this embodiment, the window W is positioned so that the left end of the window W coincides with the position P of the pixel in the SI direction, and the signal value of the profile is replaced. However, the signal value of the profile may be replaced by positioning the window W such that a position different from the left end of the window W (for example, the right end of the window W) matches the position P of the pixel in the SI direction.

Further, in this embodiment, the signal value of the profile F _n, is replaced with the maximum value of the signal in the window W. However, if the detection error of the position of the edge of the liver can be reduced, the signal value of the profile F _n is different from the maximum value of the signal in the window W (for example, the signal value in the window W). (Intermediate value) may be substituted.

  In the first mode, the window width x (see FIG. 16) of the window W is set wider than the slice thickness. By setting the window width x wider than the slice thickness, when the window W is set in the signal decrease region R, a signal value larger than the signal value of the signal decrease region R can be included in the window W. . Therefore, since the signal drop region R can be replaced with a large signal value, erroneous detection of the edge position can be prevented. However, the window width x may be narrower than the slice thickness as long as erroneous detection of the position of the liver edge can be prevented.

  In the first embodiment, the position of the edge of the liver is detected by detecting the falling edge of the signal value of the profile after the filtering process. However, instead of detecting the fall of the signal value, a template of the profile after filtering is prepared, and the position of the edge of the liver is detected based on the correlation between the template and the profile after filtering. Good. Furthermore, a position different from the edge of the liver (for example, the position of the center of gravity of the liver) may be detected.

(2) Second form In the profile obtained in the first form, the signal value does not decrease in the vicinity of the edge of the liver. However, depending on the position of the slice, the signal value in the vicinity of the edge of the liver may decrease. FIG. 18 shows an example when the signal value near the edge of the liver is lowered. When the signal value in the vicinity of the liver edge decreases, even if the profile _Fn is filtered, the signal value in the vicinity of the liver edge cannot be replaced with a sufficiently large signal value. FIG. 19 schematically shows a profile F _n ′ after filtering. In FIG. 19, the signal value at a position away from the edge of the liver is replaced with a sufficiently large signal value by filtering, but the signal value at the position near the edge remains a small signal value. Therefore, the two signal value falling edges E1 and E2 appear at different positions in the vicinity of the liver edge, so that the position of the liver edge may be erroneously detected.

  Therefore, in the second embodiment, an edge detection method is devised so that the position of the liver edge is not erroneously detected even if a plurality of signal values fall in the vicinity of the liver edge. Below, a 2nd form is demonstrated.

FIG. 20 is a schematic diagram of an MR apparatus according to the second embodiment.
The MR device 200 according to the second embodiment is different from the MR device 100 according to the first embodiment in the detection means 73, but the other configurations are the same as those in the first embodiment. Therefore, in describing the MR apparatus 200 of the second embodiment, the detection means 73 will be mainly described.
The detection unit 73 includes a search range setting unit 731 to a second edge position detection unit 733.

  The search range setting unit 731 sets a search range in the profile filtered by the filter unit 72.

  The first edge position detection means 732 obtains a first threshold value T1 of the signal value of the filtered profile, and detects the temporary position of the liver edge from the search range based on the first threshold value T1. To do.

  The second edge position detection means 733 obtains a second threshold value T2 of the signal value of the filtered profile, and detects the position of the liver edge from the search range based on the second threshold value T2.

The control unit 7 is an example of a unit that constitutes the conversion unit 71 to the detection unit 73, and functions as these units by executing a predetermined program.
The liver edge detection process in the second embodiment will be described below.

FIG. 21 to FIG. 24 are explanatory diagrams when the position of the edge of the liver is detected from the profile F _n ′ after filtering.
The search range setting means 731 (see FIG. 20) sets the first search range W1 in the filtered profile F _n ′. FIG. 21 shows an example of the first search range W1. Conditions necessary for setting the first search range W1 (for example, the position and width of the first search range W1) can be determined by the operator before executing the main scan SC3. For example, the operator can determine conditions such as the position and width of the first search range W1 when setting the navigator region R _nav in step ST2. The search range setting means 731 sets the first search range W1 in the filtered profile F _n ′ based on the condition determined by the operator. The width of the first search range W1 can be set to 10 cm, for example. After setting the first search range W1, a temporary position of the edge of the liver is detected from the search range W1 (see FIG. 22).

FIG. 22 is an explanatory diagram when a temporary position of the edge of the liver is detected from the search range W1.
The first edge position detecting means 732 (see FIG. 20) first obtains a threshold value T1 used when detecting the temporary position of the liver edge. The threshold value T1 is obtained by the following equation, for example.
T1 = (Max−Min) * k1 + Min (1)
Here, Max: the maximum value of the signal value of the profile F _n ′ in the search range W1
Min: Minimum value of signal value of profile F _n ′ in search range W1
k1: coefficient

The value of the coefficient k1 in Expression (1) is, for example, k1 = 0.5. Substituting k1 = 0.5 into the equation yields:
T1 = (Max−Min) * 0.5 + Min (2)

When the threshold value T1 is obtained using Expression (2), an intermediate value between the maximum value Max and the minimum value Min of the profile F _n ′ is obtained as the threshold value T1.

Next, the first edge position detecting means 732, from the signal value of the search range W1, greater than the threshold value T1, and detects the closest signal value S _t1 to the threshold T1. The position of the signal value S _t1, detects as the position E _t1 tentative liver edge. After detecting the position E _t1 tentative liver edge, the position E _t1 tentative liver edge as a reference, to set the second search range for detecting the position of the liver edge (see FIG. 23 ).

FIG. 23 is a diagram illustrating an example of the second search range W2.
Search range setting means 731, a position E _t1 tentative liver edge as a reference, to set the second search range W2. Here, the second search range W2 is set on the lung side from the provisional position _Et1 of the liver edge. The width of the second search range W2 is set to about twice the slice thickness, for example. After setting the first search range W2, the position of the edge of the liver is detected from the search range W2 using a threshold T2 different from the threshold T1 (see FIG. 24).

FIG. 24 is an explanatory diagram when the position of the edge of the liver is detected from the search range W2.
First, the second edge position detection means 733 (see FIG. 20) obtains a threshold T2 used when detecting the position of the liver edge from the second search range W2. The threshold value T2 can be expressed by the following equation.
T2 = (Max−Min) * k2 + Min (3)

However, in the case of T2, the value of the coefficient k2 is set to a value smaller than the coefficient k1 of the threshold value T1. For example, k2 = 0.2. Substituting k2 = 0.2 into equation (3) yields the following equation:
T2 = (Max−Min) * 0.2 + Min (4)

  When the threshold value T2 is obtained using Expression (4), a value smaller than the threshold value T1 is obtained as the value of T2.

Next, the second edge position detecting means 733, from the signal value of the search range R2, larger than the threshold value T2, and detects the closest signal value S _t2 to the threshold T2. The position of this signal value _St2 is detected as the position of the liver edge.

In the second embodiment, the provisional position _Et1 of the liver edge is detected based on the threshold T1, the search range W2 is set based on the provisional position _Et1 of the edge, and then based on another threshold T2. A liver edge position _Et2 is detected from the search range W2. Therefore, even if the signal value decreases near the edge of the liver, the detection error of the edge position can be reduced.

  In the second form, the width of the search range W2 is set wider than the slice thickness. By setting the width of the search range W2 wider than the slice thickness, even if the signal value decreases near the edge of the liver, the fall of the signal that occurs near the position of the liver edge is detected in the search range W2. Can be included. Therefore, erroneous detection of the position of the liver edge can be prevented. In this embodiment, the width of the search range W2 is set wider than the slice thickness. However, if it is possible to prevent erroneous detection of the position of the edge of the liver, the search range W2 is narrower than the slice thickness. Also good.

In the second mode, the first search range W1 is set based on information manually input by the operator. However, the search range setting means 731 may set automatically based on the setting position of the size and navigator region R _nav navigator region R _nav.

In the second embodiment, the first search range W1 is set in the filtered profile, and the provisional position _Et1 of the liver edge is detected from the first search range W1. However, the entire range in the SI direction of the profile after the filtering process is set as the first search range W1, and the temporary position E _t1 of the liver edge is detected from the entire range in the SI direction of the profile. Good.

(3) Third embodiment In the second embodiment, the profile is filtered, and the edges of the liver are detected using the threshold values T1 and T2 for the filtered profile. In the third embodiment, An example in which the edge of the liver is detected without filtering the profile will be described.

FIG. 25 is a schematic view of an MR apparatus according to the third embodiment.
The MR device 300 of the third embodiment is different from the MR devices of the first and second embodiments in the control unit 7, but the other configurations are the same as those in the first and second embodiments. Therefore, in describing the MR device 300 of the third embodiment, the control unit 7 will be mainly described.
The control unit 7 includes conversion means 71, detection means 73, and the like.

The conversion means 71 converts the navigator signal into a real space profile.
The detection means 73 detects the position of the edge of the liver. The detection unit 73 includes a search range setting unit 731 to a second edge position detection unit 733.

  The search range setting unit 731 sets a search range in the profile obtained by the conversion unit 71.

  The first edge position detection means 732 obtains a first threshold value T1 of the signal value of the profile, and detects a temporary position of the edge of the liver from the search range based on the first threshold value T1.

  The second edge position detection means 733 obtains a second threshold value T2 of the signal value of the profile, and detects the position of the edge of the liver from the search range based on the second threshold value T2.

  The control unit 7 is an example of a unit constituting the conversion unit 71 and the detection unit 73, and functions as these units by executing a predetermined program.

  26 to 30 are explanatory diagrams when the position of the edge of the liver is detected in the third embodiment.

Figure 26 is a diagram showing a profile F _n obtained by converting the navigator signal S _n.
In Figure 26, at a position away from the liver edge is not a decrease in the signal so large in the vicinity of the liver edge is example of the profile F _n the signal is greatly reduced is shown schematically. After obtaining the profile _{F n,} the search range setting means 731 (see FIG. 25) sets the first search range W1 to profile _{F n.} FIG. 27 shows an example of the first search range W1. Conditions necessary for setting the first search range W1 (for example, the position and width of the first search range W1) can be determined by the operator before executing the main scan SC3. For example, the operator can determine conditions such as the position and width of the first search range W1 when setting the navigator region R _nav in step ST2. Search range setting means 731, based on the conditions the operator has decided to set the first search range W1 to profile F _n. The width of the first search range W1 can be set to 10 cm, for example. After setting the first search range W1, the temporary position of the liver edge is detected from the search range W1 (see FIG. 28).

FIG. 28 is an explanatory diagram for detecting a temporary position of the edge of the liver from the search range W1.
The first edge position detection means 732 (see FIG. 25) first obtains a threshold value T1 used when detecting the temporary position of the liver edge. The threshold value T1 is obtained by the following equation, for example.
T1 = (Max−Min) * k1 + Min (5)
Here, Max: the maximum value of the signal value of the profile F _n in the search range W1
Min: Minimum value of signal value of profile F _n in search range W1
k1: coefficient

The value of the coefficient k1 in Expression (5) is, for example, k1 = 0.5. Substituting k1 = 0.5 into the equation yields:
T1 = (Max−Min) * 0.5 + Min (6)

When obtaining the threshold value T1 using the equation (6), an intermediate value between the maximum value Max and the minimum value Min of the profile _{F n} is obtained as a threshold value T1.

Next, the first edge position detecting means 732, from the signal value of the search range W1, greater than the threshold value T1, and detects the closest signal value S _t1 to the threshold T1. The position of the signal value S _t1, detects as the position E _t1 tentative liver edge. After detecting the position E _t1 tentative liver edge, the position E _t1 tentative liver edge as a reference, to set the second search range for detecting the position of the liver edge (see FIG. 29 ).

FIG. 29 is a diagram illustrating an example of the second search range W2.
The search range setting means 731 (see FIG. 25) sets the second search range W2 with reference to the provisional position _Et1 of the liver edge. Here, the second search range W2 is set on the lung side from the provisional position _Et1 of the liver edge. The width of the second search range W2 is set to about twice the slice thickness, for example. After setting the second search range W2, the position of the edge of the liver is detected from the search range W2 using a threshold T2 different from the threshold T1 (see FIG. 30).

FIG. 30 is an explanatory diagram when the position of the edge of the liver is detected from the search range W2.
First, the second edge position detecting means 733 (see FIG. 25) obtains a threshold value T2 used when detecting the position of the liver edge from the second search range W2. The threshold value T2 can be expressed by the following equation.
T2 = (Max−Min) * k2 + Min (7)

However, in the case of T2, the value of the coefficient k2 is set to a value smaller than the coefficient k1 of the threshold value T1. For example, k2 = 0.2. Substituting k2 = 0.2 into equation (3) yields the following equation:
T2 = (Max−Min) * 0.2 + Min (8)

  When the threshold value T2 is obtained using Expression (8), a value smaller than the threshold value T1 is obtained as the value of T2.

Next, the second edge position detection means 733 detects a signal value that is larger than the threshold value T2 and closest to the threshold value T2 from the signal values in the search range W2. In FIG. 30, it is assumed that the signal value _St2 is detected. Therefore, the second edge position detecting means 733 detects the position of the signal value _{St2 as} the position of the liver edge _Et2 .

In the profile F _n in the third embodiment, the signal decrease is not so large at a position away from the edge of the liver. In such a case, the two threshold values T1 and T2 may be applied to the unfiltered profile to detect the position of the liver edge.

In the first to third embodiments, the reference position P _ref is the position of the edge of the liver when the subject finishes exhaling. However, the reference position P _ref is not limited to the position of the edge of the liver when the subject finishes exhaling. For example, the reference position P _ref is set to the position of the edge of the liver when the subject finishes inhaling. Alternatively, it may be set to the position of the edge of the liver while the subject is inhaling or exhaling.

In the first to third embodiments, n navigator sequences A _{1 to An} and n imaging sequences B _{1 to} B _n are executed in the main scan SC3. However, the number of times that the navigator sequence is executed need not be the same as the number of times that the imaging sequence is executed, and may be different. For example, one navigator sequence and a plurality of (for example, two) imaging sequences may be executed alternately. In this case, slice tracking in a plurality of imaging sequences may be executed based on the position of the edge of the liver obtained by one navigator sequence. Further, in the first to third embodiment, the collecting data of the k-space slices _SL 1 to SL _m in one imaging sequence, k for some slices of the slice _SL 1 to SL _m Spatial data may be collected.

In the first to third embodiments, the reference position _Pref is obtained based on the data obtained by the prescan SC2, but the navigator sequence that is executed at the beginning of the main scan SC3 without executing the prescan SC2. the position of the edge of the liver obtained in a _1, may be used as the reference position _{P ref.}

  In the first to third embodiments, the main scan SC3 is a slice tracking scan that corrects the position of the slice, but the present invention is not limited to this, and a scan that does not perform slice tracking (for example, the liver) The present invention can also be applied to a case where a scan that collects k-space data is executed only when the edge reaches the reference position.

  In the first to third embodiments, the position of the edge of the liver is detected. However, as long as the body movement of the subject can be detected, the position of the edge of a part other than the liver may be detected. In the first to third embodiments, the imaging region is the liver, but the present invention can also be applied when a region other than the liver (for example, the kidney) is used as the imaging region.

2 Magnet 3 Table 3a Cradle 4 Receiving coil 5 Transmitter 6 Gradient magnetic field power supply 7 Control unit 8 Operation unit 9 Display unit 10 Subject 21 Bore 71 Conversion unit 72 Filter unit 73 Detection unit 100, 200, 300 MR apparatus 731 Search range setting Means 732 First edge position detection means 733 Second edge position detection means

Claims (10)

A magnetic resonance apparatus that sets a slice at a predetermined part and acquires image data of the predetermined part,
A collecting means for collecting a navigator signal including position information of the predetermined part from a navigator region including at least a part of the predetermined part;
Conversion means for converting the navigator signal into a profile in real space;
Filter means for setting a window at each position of the profile and filtering the profile based on a signal value in the window, and setting a window width of the window based on a slice thickness of the slice Filter means;
Detection means for detecting the position of the predetermined part based on the filtered profile;
A magnetic resonance apparatus. The filter means includes
The magnetic resonance apparatus according to claim 1, wherein the window width is set wider than the slice thickness. The detection means includes
First edge position detecting means for obtaining a first threshold value of the signal value of the filtered profile and detecting a temporary position of an edge of the predetermined part based on the first threshold value;
Search range setting means for setting an edge search range of the predetermined part in the filtered profile based on the temporary position of the edge;
Second edge position detection for obtaining a second threshold value of the signal value of the filtered profile and detecting the position of the edge of the predetermined part from the search range based on the second threshold value The magnetic resonance apparatus according to claim 1, further comprising: means.   The magnetic resonance apparatus according to claim 3, wherein the search range is set wider than a slice thickness. The first edge position detecting means includes
The magnetic resonance apparatus according to claim 3, wherein a temporary position of the edge is detected from a search range different from the search range. A collecting means for collecting a navigator signal including position information of the predetermined part from a navigator area including an edge of the predetermined part;
Conversion means for converting the navigator signal into a profile in real space;
A magnetic resonance apparatus having detection means for detecting a position of an edge of the predetermined part based on the profile,
The detection means includes
First edge position detecting means for obtaining a first threshold value of the signal value of the profile and detecting a temporary position of an edge of the predetermined portion based on the first threshold value;
Search range setting means for setting an edge search range of the predetermined part in the profile based on the provisional position of the edge;
Second edge position detecting means for obtaining a second threshold value of the signal value of the profile and detecting an edge position of the predetermined part from the search range based on the second threshold value; A magnetic resonance apparatus.   The magnetic resonance apparatus according to claim 6, wherein the search range is set wider than a slice thickness. The first edge position detecting means includes
The magnetic resonance apparatus according to claim 6, wherein a temporary position of the edge is detected from a search range different from the search range. A magnetic resonance apparatus that sets a slice at a predetermined part, acquires image data of the predetermined part, and collects a navigator signal including position information of the predetermined part from a navigator region including at least a part of the predetermined part The program of
A conversion process for converting the navigator signal into a profile in real space;
A filter process for setting a window having a window width determined based on a slice thickness of the slice at each position of the profile, and filtering the profile based on a signal value in the window;
A detection process for detecting the position of the predetermined part based on the filtered profile;
A program to make a computer execute. A program of a magnetic resonance apparatus that collects a navigator signal including position information of the predetermined part from a navigator area including an edge of the predetermined part,
A conversion process for converting the navigator signal into a profile in real space;
A program for causing a computer to execute detection processing for detecting a position of an edge of the predetermined part based on the profile;
The detection process includes
A first edge position detection process for obtaining a first threshold value of the signal value of the profile and detecting a temporary position of an edge of the predetermined part based on the first threshold value;
A search range setting process for setting a search range for the edge of the predetermined part in the profile based on the temporary position of the edge;
A second edge position detection process for obtaining a second threshold value of the signal value of the profile and detecting an edge position of the predetermined part from the search range based on the second threshold value. program.

Images