JP2022164567A - Magnetic resonance imaging device and magnetic resonance imaging method - Google Patents

Abstract

To improve the consistency in the imaging direction between oblique images that have the same oblique type but have the different imaging protocols.SOLUTION: A magnetic resonance imaging device comprises: image acquisition means; geometry parameter generation means; oblique image decision means; and oblique image generation means. The image acquisition means acquires the pilot image three-dimensional volume data. The geometry parameter generation means generates a geometry parameter including the imaging direction of the oblique image. The oblique image decision means decides the plurality of imaging protocols and oblique types of the oblique image according to an inspection order. The oblique image generation means generates the plural types of oblique images corresponding to the plurality of imaging protocols and oblique types by using the geometry parameter to each regular three-dimensional volume data acquired for each imaging protocol.SELECTED DRAWING: Figure 1

Description

The embodiments disclosed in the specification and drawings relate to a magnetic resonance imaging apparatus and a magnetic resonance imaging method.

When acquiring medical images using a magnetic resonance imaging apparatus, it is usually necessary to acquire oblique images suitable for observing different parts of the body.

An oblique image is divided into a plurality of oblique types such as oblique sagittal, oblique coronal, and oblique axial according to the imaging direction, and each oblique type has different uses. Taking the knee as an example, an oblique sagittal image parallel to the outer edge of the femoral condyle is suitable for observing the posterior cruciate ligament (PCL) and passes through multiple epicondyles. Both the oblique sagittal image and the oblique coronal image parallel to the line of movement are suitable for observing the anterior cruciate ligament (ACL), and the oblique axial image is an anterior medial bundle of the anterior cruciate ligament (anteromedial bundle: The AM and posterolateral (PL) bundles can be clearly delineated, and the anteromedial and posterolateral bundles can be evaluated separately.

In addition, when obtaining an oblique image using a magnetic resonance imaging device, longitudinal relaxation-weighted imaging (T1 weighted imaging: T1WI) and transverse relaxation-weighted imaging (T2 weighted imaging: T2WI), proton density weighted imaging (PDWI), FLAIR (fluid attenuated inversion recovery) imaging, diffusion weighted imaging (DWI), perfusion weighted imaging (PWI), etc. Acquire an oblique image of the target imaging site using one or more of the following imaging protocols.

Conventionally, there is a magnetic resonance imaging apparatus that directly acquires a two-dimensional image as an oblique image. In such a magnetic resonance imaging apparatus, it is usually necessary to acquire oblique images of different oblique types for each predetermined imaging protocol. become peace. Supposing that there are three imaging protocols to be performed on a certain body part and there are two oblique types corresponding to each imaging protocol, the total number of oblique image imagings is six. This can lead to the problem that the total imaging time of the oblique image is too long.

There is also a medical image processing apparatus that acquires three-dimensional volume data and post-processes it to generate an oblique image. In such a medical image processing apparatus, landmarks are detected for different three-dimensional volume data corresponding to different imaging protocols. Given imaging geometry parameters such as field of view (FOV), oblique images of one or more oblique types corresponding to each imaging protocol are generated.

However, in such post-processing, the feature points that can be acquired are different for each different imaging protocol. In some cases, the desired feature point cannot be detected. As a result, the oblique images generated for different imaging protocols may have different imaging directions, which may lead to the problem that the imaging directions do not match between oblique images of the same oblique type but different imaging protocols. .

U.S. Pat. No. 7,693,321 WO2010/150783 WO2013/027540 JP 2012-101045 A

One of the problems to be solved by the embodiments disclosed in the specification and drawings is to improve the matching of imaging directions between oblique images of the same oblique type but different imaging protocols. However, the problems to be solved by the embodiments disclosed in this specification and drawings are not limited to the above problems. A problem corresponding to each effect of each configuration shown in the embodiments described later can be positioned as another problem.

A magnetic resonance imaging apparatus according to an embodiment includes image acquisition means, geometry parameter generation means, oblique image determination means, and oblique image generation means. The image acquiring means acquires pilot image three-dimensional volume data from which the anatomical structure can be recognized with respect to the imaging region of the subject. A geometry parameter generating means generates geometry parameters including the imaging direction of the oblique image based on the feature points detected from the pilot image three-dimensional volume data. The oblique image determining means determines a plurality of imaging protocols of the oblique image and an oblique type corresponding to each of the imaging protocols according to an examination order for the imaging region. The oblique image generation means generates a plurality of types of oblique images corresponding to the plurality of imaging protocols and the oblique types using the geometry parameters for each of the formal three-dimensional volume data acquired for each of the imaging protocols. Generate.

FIG. 1 is a functional block diagram showing the magnetic resonance imaging apparatus according to the first embodiment. FIG. 2 is a flow chart showing the flow of the magnetic resonance imaging method performed by the magnetic resonance imaging apparatus according to the first embodiment. FIG. 3A is a schematic diagram showing an axial image of the knee obtained based on pilot image three-dimensional volume data. FIG. 3B is a schematic diagram showing that feature points are recognized from the axial image of the knee. FIG. 4 is a schematic diagram illustrating identifying the imaging direction of an oblique image based on the detected feature points. FIG. 5 is a diagram showing an example of geometry parameters for a knee oblique image. FIG. 6 is a functional block diagram showing the magnetic resonance imaging apparatus according to the second embodiment. FIG. 7 is a flow chart showing the flow of the magnetic resonance imaging method performed by the magnetic resonance imaging apparatus according to the second embodiment. FIG. 8 is a diagram showing an example of conversion of geometry parameters.

Hereinafter, embodiments of a magnetic resonance imaging apparatus and a magnetic resonance imaging method will be described in detail with reference to the drawings.

A magnetic resonance imaging apparatus according to one embodiment includes image acquisition means for acquiring pilot image three-dimensional volume data capable of recognizing the anatomy of an imaging region of a subject; Geometry parameter generation means for generating geometry parameters including an imaging direction of the oblique image based on the detected feature points; and a plurality of imaging protocols for the oblique image and the imaging protocols according to an examination order for the imaging region. Oblique image determination means for determining an oblique type corresponding to each; and an oblique image generating means for generating a plurality of types of oblique images corresponding to.

In the magnetic resonance imaging apparatus according to one embodiment, the geometry parameter includes an imaging direction parameter, the imaging direction parameter corresponds to the oblique type, and the oblique image generation means corresponds to each of the imaging protocols. For each formal 3D volume data, the geometry parameters, including the imaging orientation parameters, are used to generate an oblique image of the oblique type corresponding to the imaging protocol.

In a magnetic resonance imaging apparatus according to an embodiment, the geometry parameters further include an imaging position parameter, the imaging position parameter corresponding to the imaging direction parameter, the imaging position parameter including an imaging field center point and an imaging Contains information that indicates the range.

A magnetic resonance imaging apparatus according to one embodiment aligns the pilot image 3D volume data with the formal 3D volume data, and converts the geometry parameters to the formal 3D volume data according to the result of the alignment. Further comprising geometry parameter conversion means for converting into geometry parameters corresponding to each of the dimensional volume data, the oblique image generation means uses the converted geometry parameters and the formal three-dimensional volume data to generate the plurality of types of obliques. Generate an image.

In the magnetic resonance imaging apparatus according to one embodiment, the pilot image 3D volume data is 3D volume data acquired with an imaging protocol that allows recognition of the anatomical structure of the imaging region.

In the magnetic resonance imaging apparatus according to one embodiment, the oblique type includes at least one of oblique coronal, oblique sagittal, and oblique axial, and the imaging protocol includes longitudinal relaxation-weighted imaging, transverse relaxation-weighted imaging, proton density At least one of weighted imaging, fluid attenuated inversion recovery (FLAIR) imaging, diffusion weighted imaging, and perfusion weighted imaging is included.

A magnetic resonance imaging method according to one embodiment includes an image acquisition step of acquiring pilot image three-dimensional volume data capable of recognizing an anatomy for an imaging region of a subject; A geometry parameter generation step of generating geometry parameters including an imaging direction of the oblique image based on the detected feature points; an oblique image determination step of determining an oblique type corresponding to each; a formal image acquisition step of acquiring formal three-dimensional volume data for each of the imaging protocols for the imaging site; generating a plurality of types of oblique images corresponding to the imaging protocol and the oblique type for the formal three-dimensional volume data, using the geometry parameters.

A magnetic resonance imaging method according to one embodiment aligns the pilot image 3D volume data with each of the one or more formal 3D volume data, and depending on the result of the alignment, the geometry parameter into one or more sets of geometry parameters respectively corresponding to one or more of the formal three-dimensional volume data, wherein in the oblique image generating step, the transformed geometry parameters and the formal The plurality of types of oblique images are generated using the three-dimensional volume data.

According to the magnetic resonance imaging apparatus and the magnetic resonance imaging method according to one embodiment, since oblique images for imaging sites are generated using the same geometry parameters for different imaging protocols, a plurality of types of oblique images with the same imaging direction are used. Images can be automatically generated. This makes it possible to generate an oblique image that matches the imaging direction of another imaging protocol even for an imaging protocol in which feature points are difficult to detect.

Further, according to the magnetic resonance imaging apparatus and the magnetic resonance imaging method according to one embodiment, compared with the magnetic resonance imaging apparatus that directly acquires a two-dimensional image as an oblique image, one three-dimensional volume for each imaging protocol , and the time required for imaging all oblique images can be greatly reduced.

Further, according to the magnetic resonance imaging apparatus and the magnetic resonance imaging method according to one embodiment, the conversion processing executed by the geometry parameter conversion means generates a plurality of sets of data that more closely match the formal three-dimensional volume data based on the same geometry parameters. By generating geometry parameters and generating multiple types of oblique images of the imaging site, errors in the imaging direction due to differences between each 3D volume data are further removed, and multiple types of obliques with more consistent imaging directions are obtained. Images can be automatically generated. In particular, when the imaging region is the chest, heart, abdomen, etc., the imaging region fluctuates with respiration and pulsation. can greatly improve the performance.

(First embodiment)
A magnetic resonance imaging apparatus 10 according to a first embodiment will be described below with reference to FIGS. 1 to 5. FIG.

FIG. 1 is a functional block diagram showing a magnetic resonance imaging apparatus 10 according to the first embodiment.

For example, as shown in FIG. 1, the magnetic resonance imaging apparatus 10 includes storage means 100, image acquisition means 200, feature point detection means 300, geometry parameter generation means 400, oblique image determination means 500, and oblique image generation means 600. .

The storage means 100 in this embodiment stores various data. Specifically, the storage unit 100 stores magnetic resonance data, three-dimensional volume data, image data, and the like for each subject (eg, human body). The storage unit 100 is implemented by, for example, a RAM (Random Access Memory), a semiconductor memory device such as a flash memory, a hard disk, an optical disk, or the like.

The image acquisition means 200, the feature point detection means 300, the geometry parameter generation means 400, the oblique image determination means 500, and the oblique image generation means 600 in this embodiment are implemented by, for example, a processor. In that case, each processing function described above is stored in the storage means 100 in the form of a computer-executable program, for example. Then, the processor reads and executes each program from the storage means 100, thereby realizing processing functions corresponding to each program. Also, instead of storing the program in the storage means 100, the program may be directly installed in the circuit of the processor. In that case, the processor implements the function by reading and executing the program embedded in the circuit.

The magnetic resonance imaging apparatus 10 in FIG. 1 shows only each functional configuration related to this embodiment, and although not shown, the magnetic resonance imaging apparatus 10 includes a bed, a bed control circuit, an input device, a display, and the like. is further provided with another mechanism of

The image acquisition means 200 acquires three-dimensional volume data for an imaging region of a subject. More specifically, the image acquisition means 200 generates a high-frequency magnetic field, receives magnetic resonance signals emitted from the subject under the influence of the high-frequency magnetic field, generates magnetic resonance data based on the detected magnetic resonance signals, Magnetic resonance data are stored in the storage means 100 . These functions of the image acquisition means 200 are realized by, for example, a static magnetic field magnet, a static magnetic field power supply, a gradient magnetic field coil, a gradient magnetic field power supply, a transmission coil, a transmission circuit, a reception coil, and a reception circuit (not shown).

The image acquiring means 200 obtains three-dimensional volume data after arranging the magnetic resonance data of the imaging region of the subject in a three-dimensional space, and stores the three-dimensional volume data of the imaging region of the subject in the storage means 100 as well. . The function of the image acquisition means 200 to generate three-dimensional volume data is implemented by, for example, a processor.

The feature point detection means 300 detects feature points in the three-dimensional volume data of the subject. The feature point means an anatomical landmark and is also called an anatomical landmark. The human body contains a large number of feature points, and the positions and shapes of these feature points on the body are largely determined by age, adult/child, male/female, body weight, height, and other physiques. The feature point detection means 300 recognizes the feature points from the image based on the three-dimensional volume data, for example, by image processing such as pattern recognition. For example, cardiac features include the base, apex, mitral valve, blood vessels, and the like.

A geometry parameter generating means 400 generates geometry parameters for an oblique image based on feature points detected from three-dimensional volume data. For example, the geometry parameters include the imaging direction, imaging position, etc. of the oblique image.

The oblique image determining means 500 determines a plurality of imaging protocols of oblique images and an oblique type corresponding to each of the imaging protocols according to an examination order for an imaging region of a subject.

Here, the storage means 100 described above further stores an imaging sequence repository (also called an "examination sequence repository"). The imaging sequence repository contains preset imaging sequences for each organ or site. Here, the imaging sequence repository may contain multiple imaging sequences for each organ or site, depending on the imaging purpose. Each imaging sequence defines at least an oblique image imaging protocol and an oblique type corresponding to each imaging protocol. Then, the oblique image determination means 500 searches the imaging sequence repository in the storage means 100 using the examination site of the subject specified in the examination order, and obtains the imaging protocol corresponding to the examination site and each imaging protocol. Determine the corresponding oblique type.

Table 1 below is an example of an imaging sequence repository stored in storage means 100 .

For example, as shown in Table 1, the storage means 100 stores imaging sequences such as "general examination", "cruciate ligament", and "meniscus" for the knee. For example, the “cruciate ligament” imaging sequence includes three imaging protocols, T1WI, T2WI, and PDWI, as imaging protocols for oblique images, and oblique sagittal, oblique coronal, and oblique axial as oblique types corresponding to T1WI. , oblique types corresponding to T2WI including oblique sagittal and oblique coronal, and oblique types corresponding to PDWI including oblique sagittal and oblique coronal.

The oblique image generation means 600 uses the geometry parameters generated by the geometry parameter generation means 400 for the three-dimensional volume data acquired by the image acquisition means 200, and the imaging protocol and the imaging protocol determined by the oblique image determination means 500. Generate multiple types of oblique images corresponding to oblique types.

A process of generating a plurality of types of oblique images will be described below, taking as an example the case where the imaging region of the subject is the cruciate ligament of the knee (right knee).

FIG. 2 is a flow chart showing the flow of the magnetic resonance imaging method performed by the magnetic resonance imaging apparatus 10 according to the first embodiment.

For example, as shown in FIG. 2, first, in step S11, the image acquisition means 200 is operated by the operator of the magnetic resonance imaging apparatus 10, for example, the cruciate ligament of the knee of the subject. Accept inspection orders stating that there is

Subsequently, in step S12, the image acquiring means 200 acquires pilot image three-dimensional volume data that enables recognition of the anatomical structure of the knee with respect to the cruciate ligament of the knee of the subject. At this time, the image acquiring means 200 acquires, for example, pilot image three-dimensional volume data that facilitates recognition of the anatomical structure of the knee. For example, the image acquisition means 200 sets the imaging protocol for acquiring the image to T1WI because the imaging protocol for easily recognizing the anatomical structure of the knee in pattern recognition is T1WI. to acquire pilot image three-dimensional volume data. Here, the imaging protocol of the pilot image three-dimensional volume data may be preset to an imaging protocol such as T1WI based on conventional experience. Alternatively, the storage means 100 may pre-store imaging protocols corresponding to different imaging regions, and in step S12, the image acquisition means 200 may refer to the storage means 100 to acquire the corresponding imaging protocols.

Subsequently, in step S13, the feature point detection means 300 detects feature points in the pilot image three-dimensional volume data acquired in step S12. For example, the feature point detection means 300 recognizes anatomical feature points of the knee from an image obtained based on pilot image three-dimensional volume data by pattern recognition processing.

FIG. 3A is a schematic diagram showing an axial image of the knee obtained based on pilot image three-dimensional volume data. FIG. 3B is a schematic diagram showing that feature points are recognized from the axial image of the knee.

FIGS. 3A and 3B show an example of recognizing anatomical feature points of the knee based on pilot image three-dimensional volume data.

For example, as shown in FIG. 3B, the feature point detection means 300 recognizes the posterior vertex A1 of the medial malleolus of the femur and the posterior vertex A2 of the lateral malleolus of the femur through pattern recognition processing. Recognize the lateral vertex A3 and the anterior vertex A4 in the lateral contour of the lateral malleolus.

Subsequently, in step S14, the geometry parameter generating means 400 generates geometry parameters related to the oblique image, such as the imaging direction and imaging position of the oblique image, based on the feature points detected from the pilot image three-dimensional volume data in step s13. Generate a geometry parameter containing

FIG. 4 is a schematic diagram illustrating identifying the imaging direction of an oblique image based on the detected feature points.

For example, as shown in FIG. 4, the geometry parameter generating means 400 uses the posterior vertex A1 of the medial femoral malleolus and the posterior vertex A2 of the lateral femoral malleolus to identify the oblique coronal imaging direction, The lateral apex A3 and anterior apex A4 on the lateral contour of the lateral malleolus are used to identify the imaging direction of the oblique sagittal. More specifically, the geometry parameter generating means 400 identifies the imaging direction of the oblique coronal using a line L1 passing through the posterior vertex A1 and the posterior vertex A2, and passes through the right vertex A3 and the anterior vertex A4. Line L2 is used to identify the imaging direction of the oblique sagittal.

Although not shown, the geometry parameter generating means 400 recognizes specific feature points in the sagittal image of the knee obtained based on the three-dimensional volume data of the pilot image, thereby recognizing the oblique axial shape of the knee. An imaging direction may be specified.

Further, in step S14, the geometry parameter generating means 400 specifies the imaging position of each oblique image based on the recognized feature points, in addition to specifying the imaging direction of the oblique image.

For example, as shown in FIG. 4, the geometry parameter generating means 400 generates the posterior vertex A1 of the medial femoral malleolus, the posterior vertex A2 of the lateral femoral malleolus, the right vertex A3 and the anterior vertex A4 of the lateral contour of the lateral femoral malleolus. In addition to recognizing the anterior vertex A5 of the medial femoral malleolus and the left vertex A6 of the medial femoral malleolus. Then, the geometry parameter generating means 400 identifies imaging positions such as the imaging field center point and the imaging range of the knee based on each of the recognized feature points A1 to A6.

After that, the geometry parameter generating means 400 generates geometry parameters for the oblique image according to the specified imaging direction and imaging position of the oblique image. Here, the geometry parameters relating to the oblique image are geometry parameters used when generating each oblique image, and include, for example, the imaging direction and imaging position of the oblique image.

FIG. 5 is a diagram showing an example of geometry parameters for a knee oblique image.

For example, as shown in FIG. 5, the imaging direction parameter for the oblique coronal imaging direction specified according to the direction of line L1 in FIG. is shown by the following three-dimensional coordinates representing
[Slice Direction]
X=0.30
Y=-0.94
Z = 0.06

In addition, the imaging position parameters such as the imaging field center point (denoted as "FOVCenter" in the figure) and the imaging range (denoted as "FOVSize" in the figure) calculated based on multiple feature points are as follows. It is indicated by three-dimensional spatial coordinates and spatial length.
[FOVCenter]
X=0.21
Y=0.21
Z=10.46
[FOV Size]
FovC=189.76
FovB=239.86
FOVA=239.86

Although detailed contents are omitted in FIG. 5, the geometry parameters further include geometry parameters relating to oblique sagittal and oblique axial. For the same reason, the geometry parameters for the oblique sagittal can be calculated depending on the orientation of line L2 in FIG.

Also, the geometry parameters related to the oblique axial may be specified based on the feature points A1 to A6 and/or other feature points in FIG. may be identified based on Geometry parameters corresponding to the knee oblique axial may be set in advance based on empirical values.

On the other hand, after step S11, the process proceeds to step S15. In step S15, the oblique image determining means 500 selects the knee cruciate ligament from the imaging sequence repository stored in the storage means 100 based on the knee cruciate ligament described in the examination order received in step S11. By acquiring an imaging sequence corresponding to , a plurality of imaging protocols for an oblique image and an oblique type corresponding to each of the imaging protocols are determined.

Then, the oblique image determination means 500 determines a plurality of types of oblique images corresponding to the cruciate ligament of the knee based on the determined plurality of imaging protocols and the oblique types corresponding to each imaging protocol. For example, in the example shown in Table 1, there are a total of seven types of oblique images corresponding to the cruciate ligaments of the knee, oblique sagittal T1WI images, oblique coronal T1WI images, oblique axial T1WI images, oblique sagittal T2WI images, and oblique coronal T2WI images. images, oblique sagittal PDWI images, and oblique coronal PDWI images.

Subsequently, in step S16, the image acquiring means 200 acquires formal three-dimensional volume data of the cruciate ligament of the knee. More specifically, the image acquiring means 200 acquires formal three-dimensional volume data corresponding to each imaging protocol determined in step S15. For example, the image acquisition means 200 provides formal 3D volume data corresponding to T1WI, formal 3D volume data corresponding to T2WI, and formal 3D volume data corresponding to PDWI for each imaging protocol corresponding to the cruciate ligament of the knee. Get dimensional volume data.

Subsequently, in step S17, the oblique image generating means 600 uses the geometry parameters generated in step S14 for the formal three-dimensional volume data acquired for each imaging protocol in step S16, and the geometry parameters determined in step S15. Generate multiple types of oblique images.

More specifically, the oblique image generating means 600 uses the geometry parameters including the imaging direction parameter generated in step S14 for the formal three-dimensional volume data corresponding to T1WI to obtain three types of data corresponding to T1WI. oblique images (ie, an oblique sagittal T1WI image, an oblique coronal T1WI image and an oblique axial T1WI image). In addition, the oblique image generating means 600 generates two types of oblique images corresponding to T2WI (that is, an oblique sagittal T2WI image and an oblique coronal T2WI image) using the same geometry parameters for formal three-dimensional volume data corresponding to T2WI. ). In addition, the oblique image generating means 600 generates two types of oblique images corresponding to PDWI (that is, an oblique sagittal PDWI image and an oblique coronal PDWI image) using the same geometry parameters for formal three-dimensional volume data corresponding to PDWI. ).

When generating an oblique image, in addition to the above geometry parameters, it is usually necessary to use several image reconstruction parameters including the number of slices, slice thickness, etc., but detailed explanations are omitted here. do.

According to the magnetic resonance imaging apparatus 10 according to the first embodiment described above, for three different imaging protocols of T1WI, T2WI, and PDWI, the same geometry parameters are used to generate an oblique image for the imaging site, Multiple types of oblique images with matching imaging directions can be automatically generated.

For example, an oblique sagittal T1WI image, an oblique sagittal T1WI image, an oblique sagittal T1WI image, and an oblique sagittal T1WI image are obtained by using geometry parameters for generating an oblique image based on a pilot image that makes it easy to recognize the anatomical structure of the knee for an imaging region of the cruciate ligament of the knee. The imaging directions of the T2WI image and the oblique sagittal PDWI image can be matched, and the imaging directions of the oblique coronal T1WI image, the oblique coronal T2WI image, and the oblique coronal PDWI image can be matched. This makes it possible to generate an oblique image that matches the imaging direction of another imaging protocol even for an imaging protocol in which feature points are difficult to detect (for example, T2WI).

Further, according to the magnetic resonance imaging apparatus 10 according to the present embodiment, compared with a magnetic resonance imaging apparatus that directly acquires a two-dimensional image as an oblique image, a three-dimensional volume is acquired once for each imaging protocol. , and the time required for imaging all oblique images can be greatly reduced.

(Second embodiment)
A magnetic resonance imaging apparatus 20 according to the second embodiment will be described below with reference to FIGS. 6 and 7. FIG.

FIG. 6 is a functional block diagram showing the magnetic resonance imaging apparatus 20 according to the second embodiment.

For example, as shown in FIG. 6, the magnetic resonance imaging apparatus 20 includes storage means 100, image acquisition means 200, feature point detection means 300, geometry parameter generation means 400, oblique image determination means 500, and oblique image generation means 600. , a geometry parameter conversion means 700 is provided. In the following description, detailed descriptions of the same components as in the first embodiment will be omitted, and only differences will be described.

FIG. 7 is a flow chart showing the flow of the magnetic resonance imaging method performed by the magnetic resonance imaging apparatus 20 according to the second embodiment.

For example, as shown in FIG. 7, in this embodiment, step S18 is added before step S1 for generating an oblique image of an imaging region.

In this embodiment, in step S18, the geometry parameter conversion means 700 aligns the pilot image 3D volume data acquired in step S12 with the official 3D volume data acquired in step S16, and performs the alignment. Depending on the results, the geometry parameters used for oblique image imaging are transformed into geometry parameters corresponding to the formal 3D volumetric data.

More specifically, the geometry parameter conversion means 700 performs image registration between the pilot image 3D volume data and each of the plurality of formal 3D volume data, and converts the pilot image 3D volume data and each formal 3D volume data. Transformation matrices corresponding to each of the three-dimensional volume data are generated, and each of the generated transformation matrices is used to transform each of the geometry parameters generated in step S14 into geometry parameters corresponding to each of the formal three-dimensional volume data.

FIG. 8 is a diagram showing an example of conversion of geometry parameters.

For example, as shown in FIG. 8, the geometry parameter conversion means 700 converts pilot image 3D volume data, formal 3D volume data corresponding to T1WI acquired in step S16, formal 3D volume data corresponding to T2WI, and By registering with each of the formal 3D volume data corresponding to PDWI, the geometry parameters generated in step S14 are converted into three sets of geometry parameters respectively corresponding to the three formal 3D volume data. That is, the geometry parameter conversion means 700 converts the geometry parameters generated in step S14 into geometry parameters corresponding to T1WI, geometry parameters corresponding to T2WI, and geometry parameters corresponding to PDWI.

Then, in step S17 in the second embodiment, the oblique image generating means 600 uses the three sets of geometry parameters after conversion and three formal three-dimensional volume data corresponding to each of the three sets of geometry parameters to perform step A plurality of types of oblique images corresponding to the imaging protocol and oblique type determined in S15 are generated.

More specifically, the oblique image generating means 600 uses the geometry parameters corresponding to T1WI generated in step S18 for the formal three-dimensional volume data corresponding to T1WI to obtain three types of three types corresponding to T1WI. Oblique images (ie, oblique sagittal T1WI images, oblique coronal T1WI images, and oblique axial T1WI images) are generated. In addition, the oblique image generating means 600 generates two types of oblique images corresponding to T2WI (that is, an oblique sagittal T2WI image and an oblique A coronal T2WI image) is generated. Further, the oblique image generating means 600 generates two types of oblique images corresponding to PDWI (that is, an oblique sagittal PDWI image and an oblique coronal image) using geometry parameters corresponding to PDWI for formal three-dimensional volume data corresponding to PDWI. PDWI image).

Since the acquisition time of the pilot image 3D volume data, the formal 3D volume data corresponding to T1WI, the formal 3D volume data corresponding to T2WI, and the formal 3D volume data corresponding to PDWI are different, Coordinates in three-dimensional volume data with different structures may differ.

According to the magnetic resonance imaging apparatus 20 according to the second embodiment described above, the conversion processing executed by the geometry parameter conversion means 700 generates a plurality of sets of geometries that more closely match each formal three-dimensional volume data based on the same geometry parameters. By generating parameters and generating multiple types of oblique images of the imaging site, errors in the imaging direction due to differences between each 3D volume data are further removed, and multiple types of oblique images with more consistent imaging directions. can be automatically generated. In particular, when the imaging region is the chest, heart, abdomen, etc., the imaging region fluctuates with respiration and pulsation. can be greatly improved.

(Modification)
It should be noted that, for example, the above-described embodiment can be appropriately modified and implemented.

For example, in step S14 of the first embodiment, it is described that the imaging position information of each oblique image can be identified based on the recognized feature points. In practice, the imaging position of the oblique image may be preset for different imaging sites and imaging purposes based on empirical values. Alternatively, the center point of the imaging field of view may be specified based on the recognized feature points, and then the imaging range may be set in advance based on empirical values.

In addition, the term "processor" used in the above description is, for example, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or an application specific integrated circuit (ASIC), a programmable logic device (eg, Simple Programmable Logic Device (SPLD), Complex Programmable Logic Device (CPLD), and Field Programmable Gate Array (FPGA)). When the processor is, for example, a CPU, the processor implements its functions by reading and executing a program stored in a memory circuit. On the other hand, if the processor is, for example, an ASIC, then instead of storing the program in a memory circuit, the relevant functions are built directly into the circuitry of the processor as logic circuits. Note that each processor of the present embodiment is not limited to being configured as a single circuit for each processor, and may be configured as one processor by combining a plurality of independent circuits to realize its function. good. Furthermore, a plurality of components in FIG. 1 may be integrated into one processor to realize its functions.

In addition, in the above-described embodiments and modifications, each component of each device illustrated is functionally conceptual, and does not necessarily need to be physically configured as illustrated. That is, the specific form of distribution or integration of each device is not limited to the illustrated one, and all or part of them can be functionally or physically distributed or distributed in arbitrary units according to various loads, usage conditions, etc. Can be integrated and configured. Furthermore, each processing function performed by each device may be implemented in whole or in part by a CPU and a program analyzed and executed by the CPU, or implemented as hardware based on wired logic.

Further, among the processes described in the above-described embodiment and modifications, all or part of the processes described as being automatically performed can be manually performed, or can be manually performed. All or part of the described processing can also be performed automatically by known methods. In addition, information including processing procedures, control procedures, specific names, and various data and parameters shown in the above documents and drawings can be arbitrarily changed unless otherwise specified.

According to at least one embodiment described above, it is possible to improve the matching of the imaging direction between oblique images of the same oblique type and different imaging protocols.

While several embodiments have been described, these embodiments are provided by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, changes, and combinations of embodiments can be made without departing from the scope of the invention. These embodiments and their modifications are included in the scope and spirit of the invention, as well as the scope of the invention described in the claims and equivalents thereof.

10, 20 Magnetic Resonance Imaging Apparatus 200 Image Acquisition Means 400 Geometry Parameter Generation Means 500 Oblique Image Determination Means 600 Oblique Image Generation Means 700 Geometry Parameter Conversion Means

Claims (8)

an image acquiring means for acquiring three-dimensional volume data of a pilot image from which an anatomical structure can be recognized for an imaging region of a subject;
geometry parameter generation means for generating geometry parameters including an imaging direction of an oblique image based on feature points detected from the pilot image three-dimensional volume data;
an oblique image determining means for determining a plurality of imaging protocols of the oblique image and an oblique type corresponding to each of the imaging protocols according to an examination order for the imaging site;
oblique image generation means for generating a plurality of types of oblique images corresponding to the plurality of imaging protocols and the oblique types using the geometry parameters for each of the formal three-dimensional volume data acquired for each of the imaging protocols; A magnetic resonance imaging apparatus comprising and . the geometry parameters include an imaging orientation parameter;
the imaging direction parameter corresponds to the oblique type;
The oblique image generating means generates the oblique image of the oblique type corresponding to the imaging protocol using the geometry parameters including the imaging direction parameter for each formal three-dimensional volume data corresponding to each imaging protocol. generate,
The magnetic resonance imaging apparatus according to claim 1. said geometry parameters further comprising an imaging position parameter;
the imaging position parameter corresponds to the imaging orientation parameter;
The imaging position parameters include information indicating the center point of the imaging field of view and the imaging range.
3. The magnetic resonance imaging apparatus according to claim 2. aligning the pilot image 3D volume data and the formal 3D volume data, and changing the geometry parameters to the geometry parameters corresponding to the formal 3D volume data according to the results of the alignment; further comprising a geometry parameter conversion means for converting,
The oblique image generation means generates the plurality of types of oblique images using the transformed geometry parameters and the formal three-dimensional volume data.
The magnetic resonance imaging apparatus according to claim 1. The pilot image three-dimensional volume data is three-dimensional volume data acquired with an imaging protocol capable of recognizing the anatomical structure of the imaging site.
The magnetic resonance imaging apparatus according to claim 1. the oblique type includes at least one of oblique coronal, oblique sagittal, and oblique axial;
the imaging protocol includes at least one of longitudinal relaxation-weighted imaging, transverse relaxation-weighted imaging, proton density-weighted imaging, fluid attenuated inversion recovery (FLAIR) imaging, diffusion-weighted imaging, and perfusion-weighted imaging;
The magnetic resonance imaging apparatus according to claim 1. an image acquisition step of acquiring three-dimensional volume data of a pilot image from which an anatomic structure can be recognized for an imaging region of a subject;
a geometry parameter generation step of generating geometry parameters including an imaging direction of an oblique image based on feature points detected from the pilot image three-dimensional volume data;
an oblique image determination step of determining a plurality of imaging protocols of the oblique image and an oblique type corresponding to each of the imaging protocols according to an examination order for the imaging site;
a formal image acquisition step of acquiring formal three-dimensional volume data for each post-imaging protocol for the imaging region;
and generating a plurality of types of oblique images corresponding to the imaging protocol and the oblique type using the geometry parameters for the formal three-dimensional volume data acquired for each imaging protocol. Magnetic resonance imaging method. registering the pilot image 3D volume data with each of the one or more formal 3D volume data, and depending on the result of the registration, converting the geometry parameters into one or more of the formal 3D volumes; further comprising a geometry parameter transformation step of transforming each of the data into one or more sets of geometry parameters;
In the oblique image generation step, the plurality of types of oblique images are generated using the transformed geometry parameters and the formal three-dimensional volume data.
The magnetic resonance imaging method according to claim 7.

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