Magnetic resonance imaging apparatus, reconstruction condition search method, and magnetic resonance imaging system

Abstract

To provide a technique for enabling easy setting of a reconstruction condition desired by a user when setting a reconstruction condition in an MRI apparatus.SOLUTION: Raw data obtained by an MRI apparatus or intermediate data in the middle of reconstruction is stored in a device, and only parameters related to image processing are changed later to perform reconstruction again (post-reconstruction). Means for enabling a user to input an evaluation for an image subjected to the post-reconstruction is provided, and results thereof are stored. The evaluation results are analyzed by using statistical processing or machine learning to search for a recommended reconstruction condition and to suggest the result of the search to the user.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a magnetic resonance imaging (hereinafter referred to as MRI) apparatus, and more particularly to a technique for supporting user settings of image reconstruction conditions in an MRI apparatus. [Background technology]

[0002] The contrast and the degree of artifact suppression of images obtained by MRI devices vary greatly depending on the imaging conditions and the imaging parameters set. However, the imaging parameters set in MRI include FOV, TE, TR, speed ratio, and other various parameters according to the pulse sequence used for imaging, and the image quality required varies depending on the diagnostic purpose and user preferences, so it is difficult to set imaging parameters that match the diagnostic purpose and user preferences from the many different imaging parameters.

[0003] Furthermore, in MRI, when reconstructing raw data consisting of nuclear magnetic resonance signals to produce an image, it is necessary to set various reconstruction conditions, such as selecting a reconstruction method and setting reconstruction parameters. The optimal reconstruction conditions differ depending on the imaging subject, imaging conditions, and user preferences.

[0004] For this reason, in the past, the solution was to create conditions in which various parameters were turned on and off, and repeatedly take volunteer images to get closer to the desired image quality, or to use the manufacturer's recommended parameters to avoid this tedious work.

[0005] Setting multiple parameters is essential for imaging in medical imaging devices, not limited to MRI devices, and Patent Document 1 proposes an imaging system for specifying reconstruction parameter values ​​preferred by a doctor. In this technology, after reconstructing an image, the result is fed back, the reconstruction parameters are adjusted, and reconstruction is performed once again. Feedback and re-reconstruction are repeated, and finally, reconstruction parameter values ​​desired by the doctor are determined and reconstruction is performed. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Special Publication No. 2015-510157 Summary of the Invention [Problem to be solved by the invention]

[0007] The technology disclosed in Patent Document 1 can be easily applied to imaging diagnostic devices, such as CT devices, in which raw data is relatively small in amount, such as projection data and radiographic data, but it is difficult to apply this technology to MRI devices for the following reasons. In an examination using an MRI device, a protocol is usually created that combines multiple images, and the examination is performed according to the protocol. In creating a protocol, conditions are set for each image included in the protocol, so there are a huge number of combinations of image types, such as imaged parts and contrasts. Furthermore, with the recent diversification of image filters and the sophistication of image reconstruction technology, there are also a huge number of types of image processing, so it is not realistic to apply user-preferred parameters to each one using the technology disclosed in Patent Document 1. It is also becoming extremely difficult for users to combine various functions to create their preferred images.

[0008] An object of the present invention is to provide a technique for solving the above-mentioned difficulty in optimizing reconstruction conditions in an MRI apparatus, and for easily setting reconstruction conditions desired by a user. [Means for solving the problem]

[0009] In order to solve the above problems, the present invention stores raw data in a device, and then reconstructs the image after changing only the parameters related to image processing. Hereinafter, reconstruction performed after the fact is called post-reconstruction. A means is provided that allows the user to input an evaluation of the post-reconstructed image, and the results are accumulated. The evaluation results are analyzed using statistical processing and machine learning, and the analysis results are suggested to the user.

[0010] That is, the MRI apparatus of the present invention includes an imaging unit that collects nuclear magnetic resonance signals generated by a subject, a calculation unit that generates a reconstructed image of the subject using raw data consisting of the nuclear magnetic resonance signals, and a reconstruction condition analysis unit that analyzes the reconstruction conditions of the reconstructed image. The reconstruction condition analysis unit includes an image data acquisition unit that acquires image data generated by the calculation unit, a post-reconstruction unit that uses the image data to reconstruct an image under reconstruction conditions different from the reconstruction conditions used when the calculation unit reconstructed the image, an evaluation information collection unit that presents the image reconstructed by the post-reconstruction unit, accepts user evaluations on the image, and stores the evaluation data in a database linking the user evaluations with the reconstruction conditions, and an evaluation result analysis unit that analyzes the evaluation data stored in the database and determines recommended reconstruction conditions.

[0011] The function of the post-reconstruction unit can be performed by a calculation unit that reconstructs an image.

[0012] The present invention also provides a method for presenting reconstruction conditions desired by a user in magnetic resonance imaging in which raw data consisting of nuclear magnetic resonance signals is reconstructed to generate an image, the method including a post-reconstruction step of reconstructing an image using the raw data or intermediate reconstruction data, a step of accepting a user evaluation of the generated post-reconstruction image, a step of accumulating evaluation data linking the reconstruction conditions at the time of post-reconstruction with the user evaluation of the post-reconstruction image, and a step of analyzing the accumulated evaluation data and determining recommended reconstruction conditions.

[0013] The present invention further provides a magnetic resonance imaging system including a magnetic resonance imaging apparatus that collects nuclear magnetic resonance signals generated by a subject and generates a reconstructed image of the subject, and a data processing apparatus that analyzes data acquired by the magnetic resonance imaging apparatus. The data processing apparatus includes a post-reconstruction unit that uses image data obtained by the magnetic resonance imaging apparatus to reconstruct an image under reconstruction conditions different from those of the image reconstructed by the magnetic resonance imaging apparatus, an evaluation information collection unit that presents the image reconstructed by the post-reconstruction unit, accepts user evaluations for the image, and stores the evaluation data in a database linking the user evaluations with the reconstruction conditions, and an analysis unit that analyzes the evaluation data stored in the database and searches for recommended reconstruction conditions. Effect of the Invention

[0014] According to the present invention, by storing user evaluation results for images post-reconstructed with various reconstruction parameters and analyzing the evaluation results, it is possible to present user-recommended reconstruction parameters for a combination of a large amount of raw data and a wide variety of reconstruction parameters. This makes it possible to improve image quality adjustment work in MRI and to realize efficient protocol creation combining a series of imaging scans. [Brief description of the drawings]

[0015] [Figure 1] Diagram showing the overall outline of an MRI device [Diagram 2] Computer function block diagram [Diagram 3] FIG. 1 is a diagram showing the flow of operations in the first embodiment. [Figure 4] A diagram showing details of the image reconstruction process [Diagram 5] FIG. 13 is a diagram showing an example of a reconstruction parameter setting screen in post-reconstruction. [Figure 6] FIG. 13 is a diagram showing an example of an input screen for image quality evaluation. [Figure 7] A diagram showing an example of data stored in a database. [Figure 8] FIG. 13 is a diagram showing an example of an image quality evaluation result analysis unit. [Figure 9] FIG. 13 is a diagram showing an example of a display screen for displaying recommended reconstruction conditions. [Figure 10] Functional block diagram of an image reconstruction unit according to the first modification example [Figure 11] FIG. 13 is a diagram showing a flow of a process for presenting recommended reconstruction conditions according to the first modified example. [Figure 12] Functional block diagram of a computer according to a second modification [Figure 13] Diagram showing an overview of a magnetic resonance imaging system DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] Hereinafter, an embodiment of the MRI apparatus and data processing device of the present invention will be described.

[0017] The MRI apparatus of the present invention has a function (post-reconstruction function) of reconstructing an image reconstructed by the MRI apparatus as post-processing, and at that time, accumulates reconstruction conditions at the time of post-reconstruction and user image quality evaluation information on the post-reconstructed image, and analyzes the accumulated information to search for recommended reconstruction parameters (evaluation result analysis function). The characteristic functions of the present invention are realized in a computer provided in the MRI apparatus, and in an independent data processing device connectable to the MRI apparatus. In the following embodiment, an aspect in which the post-reconstruction function and the evaluation result analysis function are realized in the computer of the MRI apparatus or an arithmetic device attached thereto will be described.

[0018] <Embodiment 1> 1, the MRI apparatus 10 includes an imaging section 100 that generates nuclear magnetic resonance in tissues (atoms) constituting a subject 101 and collects nuclear magnetic resonance signals, and a computer 200 that processes data consisting of the nuclear magnetic resonance signals acquired by the imaging section 100 and controls the entire apparatus including the imaging section 100. The computer 200 is connected to an external storage device 300 that stores data and programs required for calculations, and a user interface section (UI section) 400 for communicating with users such as doctors and medical technicians. The UI section 400 includes a display 401 and an input device 402. The computer 200 can also be connected to various databases 500 and exchanges data.

[0019] The configuration of the imaging unit 100 is similar to that of a general MRI device, and as shown in FIG. 1, includes a static magnetic field coil (static magnetic field magnet) 102 that forms a uniform static magnetic field in the imaging space, a gradient magnetic field coil 103 that provides a magnetic field gradient in three axial directions perpendicular to the static magnetic field, a shim coil 104 for correcting the uniformity of the static magnetic field, a transmitting coil 105 for irradiating a high-frequency magnetic field to the subject 101, a receiving coil 106 that receives a nuclear magnetic resonance signal generated from the subject 101, and a sequence control device 114.

[0020] The three-axis gradient magnetic field coils 103 are each connected to a gradient magnetic field power supply unit 112, and generate a gradient magnetic field according to the power supplied from the gradient magnetic field power supply unit 112. In addition, by combining the gradient magnetic fields in the three axial directions, a gradient magnetic field of any magnitude can be generated in any direction. Like the gradient magnetic field coil 103, the shim coil 104 is also driven by the shim power supply unit 113, and generates a magnetic field that cancels out errors contained in the static magnetic field generated by the static magnetic field coil 102.

[0021] The transmitting coil 105 is connected to a transmitter 107 equipped with a high-frequency magnetic field generator, a high-frequency amplifier, etc., and irradiates the subject with a high-frequency magnetic field of a predetermined frequency as an RF pulse in response to the output from the transmitter 107.

[0022] The receiving coil 106 is connected to a receiver 108 equipped with an amplifier, a quadrature detector, an A / D converter, etc. The receiver 108 samples the nuclear magnetic resonance signal using the A / D converter, and passes it as digital data to a computer 200, which is a signal processing system.

[0023] The sequence control device 114 operates the gradient magnetic field power supply unit 112, the transmitter 107, and the receiver 108 according to a predetermined pulse sequence. Various pulse sequences are stored in the device, and when imaging, the sequence control device 114 calculates a pulse sequence to be used for imaging using imaging conditions and imaging parameters set via the input device 402 or the like, and imaging is performed based on the calculated pulse sequence.

[0024] The computer 200 can be configured as a computer equipped with a CPU and a memory, and realizes functions as control units such as a measurement control unit 210 and a display control unit 240, and functions as a calculation unit such as an image reconstruction unit 220. Furthermore, the MRI apparatus 10 of this embodiment is characterized by having an image quality evaluation control unit 230 that realizes functions related to evaluation of the image quality reconstructed by the image reconstruction unit 220 and searching for recommended reconstruction conditions (function as a recommended reconstruction condition search unit).

[0025] The measurement control unit 210 controls the operation of the imaging unit 100 via the sequence control device 114. The image reconstruction unit 220 has a function of performing image reconstruction using raw data acquired by the imaging unit 100, and a function of reading the raw data or intermediate data during reconstruction once stored in the external storage device 300, and performing reconstruction again under reconstruction conditions different from the initial reconstruction conditions (hereinafter referred to as post-reconstruction).

[0026] The image quality evaluation control unit 230 has a function of collecting users' image quality evaluations (hereinafter simply referred to as user evaluations) of the image quality of images reconstructed or post-reconstructed by the image reconstruction unit 220, linking them to the reconstruction conditions of the images and storing them in the database 500, a function of analyzing the user evaluations stored in the database 500 and searching for reconstruction conditions that should be recommended to the user, and a function of determining recommended reconstruction conditions and presenting them to the user.

[0027] The display control unit 240 mainly controls the display of the UI unit 400, accepts conditions such as imaging parameters and reconstruction parameters used by the measurement control unit 210 to control the imaging unit 100, and displays images reconstructed by the image reconstruction unit 220 on the UI unit. In cooperation with the image quality evaluation control unit 230, the display controls the display for prompting the input of post-reconstruction parameters and user evaluation, and the display for presenting the evaluation results and recommended reconstruction conditions.

[0028] FIG. 2 shows an example of a functional block diagram of a computer 200 for implementing the above-mentioned functions.

[0029] As shown in the figure, the image reconstruction unit 220 includes an image data acquisition unit 221 that exchanges image data with the external storage device 300, and a reconstruction processing execution unit 222 that executes reconstruction processing using the image data. Here, the image data includes raw data and intermediate data that is processed to reconstruct a final image. The reconstruction processing performed by the reconstruction processing execution unit 222 includes a post-reconstruction using image data acquired by the image data acquisition unit 221 from the external storage device 300, in addition to a process of reconstructing under initial setting conditions, and the post-reconstruction includes a reconstruction that consistently performs from raw data to a final image, and a reconstruction that uses intermediate data to perform the remaining processes that have not been performed on the intermediate data among the multiple processes included in the reconstruction. These image data include, as auxiliary information, an imaging site, imaging conditions (imaging pulse sequence and imaging parameters), and image reconstruction conditions (processes included in the reconstruction and parameters of each process, and user information that sets the reconstruction conditions).

[0030] The external storage device 300 for storing such image data includes a storage device connected to the MRI device 10, as well as a storage device capable of exchanging data with the computer 200 of the MRI device 10, such as a cloud, and can be used in combination as appropriate.

[0031] The image quality evaluation control unit 230 includes an image quality evaluation information collecting unit (evaluation information collecting unit) 231, an image quality evaluation result analyzing unit (evaluation result analyzing unit) 232, and a recommended reconstruction condition determining unit 233. The image quality evaluation information collecting unit 231 collects evaluation data of image quality by a user via the UI unit 400 and stores it in a database. The image quality evaluation result analyzing unit 232 analyzes the collected evaluation data, and the recommended reconstruction condition determining unit 233 determines the recommended reconstruction condition, which is the analysis result. The database 500 for storing the evaluation data is not particularly limited as long as it is a large-capacity storage device capable of exchanging data with the MRI apparatus 10, similar to the external storage device 300 for storing image data. In FIG. 2, the database 500 is shown as a separate element from the external storage device 300, but the database 500 may be a part of the external storage device 300.

[0032] The image quality evaluation results can be analyzed by using techniques such as statistical analysis, such as analysis of the frequency of selection of reconstruction conditions by a given user or the distribution of evaluation values ​​constituting the evaluation data, or analysis using machine learning or deep learning (DL). In the case of machine learning, recommended reconstruction conditions can also be obtained as output. In this case, the functions of the recommended reconstruction condition determination unit 233 will be included in the image quality evaluation result analysis unit 232.

[0033] The display control unit 240 performs control for providing the UI unit 400 with a GUI for accepting instructions and evaluations from the user and processing results in executing the functions of the image reconstruction unit 220 and the image quality evaluation control unit 230 described above, and is equipped with a reconstruction parameter input unit 241 that accepts user specification of post-reconstruction parameters, an image quality evaluation information input unit 242 that presents a GUI for inputting evaluation data and accepts image quality information (evaluation data) input via the GUI, and a recommended reconstruction condition display unit 243 that presents the recommended reconstruction conditions determined by the recommended reconstruction condition determination unit 233 to the UI unit 400.

[0034] Next, the operation of the MRI apparatus of this embodiment will be described based on the above configuration. An embodiment of the operation is shown in Fig. 3. Here, an example will be described in which image reconstruction sequentially executes four processes: a process of reconstructing raw data by Fourier transform, a channel synthesis process of synthesizing data for each channel obtained by a multi-channel receiving coil, noise removal, and sensitivity correction. However, the processes included in image reconstruction are not limited to this example, and may further include other processes, such as a process for removing body movement artifacts and calculations using multiple images.

[0035] First, imaging conditions are set in the sequence control device 114 according to a user specification or a predetermined protocol (S401), and imaging is started. In setting the imaging conditions, for example, a pulse sequence used for imaging is selected, imaging parameters of the pulse sequence are set, and a reconstruction method, a correction method, and their parameters are set as conditions for image reconstruction. These imaging conditions may be set in advance as a protocol, in which case the previously set imaging conditions are read. When imaging is started according to the imaging conditions, k-space data, which is raw data, is collected (S402). The k-space data is temporarily stored in a memory in the computer 200, and reconstruction processing is performed by the image reconstruction unit 220 (reconstruction processing execution unit 222). In parallel with this processing, the image data acquisition unit 221 stores the raw data in the external storage device 300 (S403).

[0036] The image reconstruction unit 220 performs image reconstruction according to the set reconstruction conditions. For example, the raw data is Fourier transformed to convert it into real space data, and after channel synthesis, noise removal and sensitivity correction are performed (S404). The channel synthesis process executes different processes depending on the imaging conditions, such as simple multi-array coil synthesis (MAC synthesis) using the sensitivity distribution of each channel coil, parallel imaging in which data obtained by thinning out measurement is estimated using the sensitivity distribution and channel synthesis is performed, or compressed sensing.

[0037] For example, the noise removal is performed according to the reconstruction conditions, for which the filter used for noise removal and the parameters indicating the degree of noise removal are set in advance. Similarly, the sensitivity correction is performed according to the parameters such as the correction precision.

[0038] The image reconstruction unit 220 may be configured to output image data (intermediate data) at any timing in the image reconstruction algorithm and store it in the external storage device 300. FIG. 4 shows a process flow when intermediate data is stored. In this example, a decision is made for each process as to whether to store the intermediate data, and when it is decided to store the intermediate data, the image data acquisition unit 221 acquires the intermediate data as image data, but the decision step may be omitted and a predetermined or all intermediate data may be stored. After the intermediate data is stored in a storage device such as the external storage device 300, it is read out by the image reconstruction unit 220 for post-reconstruction (S408) to be described later.

[0039] The display control unit 240 causes the display 401 to display the image generated by executing the reconstruction (S405).

[0040] If post-reconstruction is not required for the displayed image (S406), imaging ends. On the other hand, if post-reconstruction is required, the process proceeds to a step for post-reconstruction and image quality evaluation. The user decides whether or not to perform post-reconstruction, and sends a command to the measurement control unit 210 via the UI unit 400, such as to end imaging, or displays a GUI for confirming whether or not post-reconstruction is required, and the user makes a selection.

[0041] In the post-reconstruction and image quality evaluation process, first, when the user sets reconstruction parameters via the UI unit 400 that are different from the reconstruction conditions used in the initial reconstruction (S404), the reconstruction parameter input unit 241 accepts these settings and passes them to the image reconstruction unit 220 (S407).

[0042] 5 shows an example of a post-reconstruction parameter reception screen displayed on the UI unit 400. In the example shown, the degree of processing for four items, namely noise removal, resolution, sensitivity correction, and correction mode, as well as the necessity of body motion correction, distortion correction, and intermediate data output, can be input as parameters to be set. The configuration may also be such that necessary settings are received for processing performed prior to these processes, such as Fourier transform and parallel imaging.

[0043] For input of parameters, for example, the parameters used for the initial reconstruction are displayed in a box to the right of each process, and it may be configured to change them and accept input of new post-reconstruction parameters. Operating the "START" button 501 confirms the input contents and proceeds to post-reconstruction. Operating the "CANCEL" button 502 also allows the input contents to be changed.

[0044] "Intermediate data output" is a command that instructs to perform post-reconstruction using data generated during each reconstruction process, and when it is "ON", the reconstruction process execution unit 222 imports the intermediate data stored in the external storage device 300 and performs reconstruction processing. If the reconstruction parameters that have been changed are, for example, only parameters related to sensitivity correction, or parameters for processing performed after sensitivity correction, the intermediate data obtained by processing before sensitivity correction is imported.

[0045] The intermediate data may be output as a part of the data rather than the entire data. For example, in the case of 3D data, intermediate data of one or more slices, which is the minimum unit required for subsequent image confirmation (S410), may be imported and reconstruction processing may be performed.

[0046] By providing a function for reading data in the middle of processing and performing post-reconstruction in this way, the image reconstruction unit 220 only needs to execute the remaining processing of the reconstruction calculation, thereby reducing the calculation load. In particular, by processing the minimum unit of intermediate data required for image confirmation, the work efficiency can be improved.

[0047] When input of reconstruction parameters for post-reconstruction is completed (for example, when the "START" button 501 is operated), the image reconstruction unit 220 reads the image data to be processed (S408) and executes post-reconstruction according to the reconstruction conditions set by the user (S409). In Fig. 3, multiple processes are shown in the block indicating post-reconstruction, but if the image data read in S408 is intermediate data, only some of the processes are executed. The display control unit 240 (image quality evaluation information input unit 242) displays the image resulting from the post-reconstruction on the display 401 (S410), and also displays a GUI for inputting the user's evaluation of the image quality.

[0048] An example of a GUI for inputting user evaluations is shown in Fig. 6. In this example, the system is configured so that the user can indicate subjective image quality indicators such as noise, blur (detail), and contrast on a five-point scale in addition to an overall evaluation of image quality. However, the image quality evaluation may be configured to accept a simpler evaluation, for example only an overall evaluation, depending on the user's level of expertise and preferences.

[0049] The user's evaluation results input via such a GUI are passed to the image quality evaluation information collecting unit 231 via the image quality evaluation information input unit 242. The image quality evaluation information collecting unit 231 accumulates the acquired evaluation results in a database together with the image capturing conditions (imaging method, imaging parameters) and information on the user who performed the evaluation (S411).

[0050] Once the image quality information has been collected, the process returns to step S406, and the steps from reconstruction parameter setting S407 to image quality evaluation information collection S411 are repeated. The repetition continues until it is determined in step S406 that post-reconstruction is not to be performed. Although only one set of raw data is obtained in one imaging session in imaging S402, post-reconstruction can be repeatedly performed as post-processing, and therefore, by repeating the process while changing the reconstruction conditions of post-reconstruction, the user can obtain an image of desired image quality, i.e., an image of good image quality that is useful for diagnosis.

[0051] The results of the user's image quality evaluation obtained for each repetition are collected by the image quality evaluation information collecting unit 231, stored in a database, and effectively used for subsequent analysis.

[0052] The analysis S412 by the image quality evaluation result analysis unit 232 is performed on the premise that sufficient data has been collected to perform statistical processing on the evaluation results. The sufficient data includes not only data obtained by repeating the above steps S407 to S411 by the same user, but also data obtained by many imaging operations and many image quality evaluations performed in the past with the same or similar MRI device. FIG. 7 shows an example of the structure of the database. Each time post-reconstruction is performed, one row of data in the table in FIG. 7 is stored. In FIG. 7, for the sake of simplicity, the items included in one row of data are limited to patient information, imaging conditions (imaging site, imaging parameters), user information, initial reconstruction parameters, changed reconstruction parameters, and image quality evaluation results, but various other information associated with the image data to be handled can be stored. The structure of the database is not limited to the table format shown in FIG. 7, and various structures can be used.

[0053] The image quality evaluation result analysis unit 232 uses a large amount of data accumulated as the three databases in this way to search for reconstruction conditions recommended for the image data currently undergoing post-reconstruction (S412). The analysis by the image quality evaluation result analysis unit 232 may involve converting each evaluation item into a numerical value and performing a statistical analysis to select the reconstruction condition that yields the highest evaluation value, or may involve analysis using machine learning such as CNN or AI.

[0054] As an example, an example using CNN is shown in Fig. 8. In this example, the initial parameters, changed parameters, frequency of use in post-reconstruction (reflecting user preferences), image quality evaluation results, etc. are input, and a CNN that has been trained to output parameters that provide the best image quality evaluation results is used, and recommended reconstruction parameters are obtained as the output of the CNN. In addition to the above-mentioned items, the input to the CNN can include imaging conditions and patient information (examination area, age, sex, etc.), in which case it is possible to output recommended reconstruction parameters according to the imaging conditions and patient information (S413).

[0055] An example of the recommended reconstruction parameters is shown in Figure 9. In the example shown, the recommended conditions for the reconstruction parameters are displayed, such as "Heavy recommend" (degree of noise removal), next to the box displaying the value of each parameter. If the set parameters match the recommended conditions, "Recommended Param." is displayed. Suggestions in the form of comments may be made if necessary.

[0056] When the recommended reconstruction parameters are determined, they are fed back to the imaging condition setting step S401 at the start of imaging. When the recommended reconstruction parameters are determined according to the imaging conditions and patient information, the reconstruction parameters recommended for the same imaging conditions are initially set, and imaging (k-space data acquisition) S402 is executed. That is, reconstruction conditions that can obtain the image quality desired by the user at the start of imaging are set.

[0057] 3, the recommended reconstruction parameters are fed back to the imaging condition setting step, but the recommended reconstruction parameters may be fed back to the reconstruction parameter setting step S407 to perform post-reconstruction again. For example, in the example shown in FIG 9, when the "START" button 502 is operated, post-reconstruction is performed again under the recommended reconstruction conditions.

[0058] As described above, the MRI apparatus of this embodiment introduces a mechanism for the user to set reconstruction condition settings and reconstruct images using original data (raw data) of an image once reconstructed or intermediate data during reconstruction, and a mechanism for accepting the user's image quality evaluation at each post-reconstruction and accumulating the user's image quality evaluation linked to the reconstruction conditions of the image, so that the MRI apparatus can present recommended reconstruction conditions to the user or automatically set them using the accumulated user evaluations. This allows the user to reduce trial and error in setting reconstruction parameters and shorten the time from the start of imaging to image output.

[0059] In addition, the MRI apparatus of this embodiment can use intermediate data obtained during the reconstruction algorithm in post-reconstruction, which reduces the burden of reconstruction calculation, shortens the time required for post-reconstruction image output, and enables the suitability of the reconstruction conditions set (evaluation of image quality) to be determined in a short time. In particular, by using the smallest unit of data as intermediate data, processing can be further simplified and time can be shortened.

[0060] <Modification> The MRI apparatus of embodiment 1 can be provided with additional functions in addition to the functions of evaluating image quality and presenting recommended reconstruction conditions described above. Below, we will explain a modified example with additional functions, focusing on the differences from embodiment 1.

[0061] <Variation 1> In this modification, a function of presenting a simulation image is added when presenting recommended reconstruction conditions.

[0062] The simulation image can be created by a program that is generally available as an "MR image simulator" that can generate an image from a human body model and any imaging parameters, such as TR and TE. In this modification, a simulation image generating unit 223 equipped with such a simulator program is added to the computer 200 or the image reconstruction unit 220, as shown in FIG.

[0063] FIG. 11 shows details of the process for presenting a simulation image (FIG. 3: steps S412 and S413).

[0064] The recommended reconstruction condition determination unit 233 acquires the imaging conditions set in the measurement control unit 21 in step 401 (S412-1), searches the database (S412-2), and determines the recommended reconstruction conditions by analyzing the evaluation data that matches the imaging conditions (S413-1). When the recommended reconstruction conditions are determined, the simulation image generation unit 223 reconstructs a simulation image of the imaging region using the initially acquired imaging conditions (TR / TE, imaging region) and the recommended reconstruction conditions (S413-2). Finally, the recommended reconstruction conditions and the simulation image are displayed on the display 401 (S413-3).

[0065] According to this modification, by presenting the recommended reconstruction conditions together with a simulation image reconstructed under those reconstruction conditions, it becomes easier for the user to visually understand whether the recommended reconstruction conditions are optimal for the user.

[0066] <Variation 2> This modification adds a function of reflecting information about body movements in determining recommended reconstruction conditions.

[0067] If an irregular event such as body movement occurs during imaging, the acquired k-space data will be affected. Various methods have been proposed for monitoring body movement in MRI systems, and methods have been established for correcting k-space data or image data according to the magnitude of the detected body movement.

[0068] In this modification, motion correction is treated as a process included in the process included in image reconstruction, and recommended reconstruction conditions are presented for whether motion correction is necessary or the degree of motion correction. For this reason, a motion determination unit 250 for determining the magnitude of motion is added to the computer 200 as shown in FIG. 12. When the MRI apparatus has a function (motion monitoring function) for acquiring motion information from an external motion monitor such as an abdominal pressure gauge or a velocity sensor, the motion determination unit 250 acquires information such as the magnitude, frequency, and period of motion based on the motion information from the motion monitor using the function, and determines whether motion correction of k-space data or image data is necessary. When imaging is performed by applying a navigator echo for the purpose of motion detection, a similar determination may be made from the navigator echo, or the determination may be made from k-space data or image data reconstructed from it. For example, in the case of image data, a part where motion has occurred has a noticeable blur or artifacts, so that motion can be determined.

[0069] The body motion determining unit 250 sends the determination result to the recommended reconstruction condition determining unit 233. If the body motion determining unit 250 determines that body motion correction is "unnecessary", the recommended reconstruction condition determining unit 233 recommends body motion correction "OFF" as the recommended reconstruction condition, and if the body motion determining unit 250 determines that body motion correction is "necessary", the recommended reconstruction condition determining unit 233 recommends body motion correction "ON" by displaying a comment such as "Body motion has been detected. 'ON' is recommended."

[0070] Furthermore, if it is determined that the level of body movement is such that body movement correction is difficult, then as shown by the dotted line in Fig. 9, a comment recommending reimaging will be displayed, for example, by displaying "Body movement has been detected. Reimaging is recommended," to recommend that the image be retaken.

[0071] According to this modified example, by including processing for body movement in the reconstruction conditions and recommending appropriate processing, it is possible to make the user aware of the need for body movement correction, and images of the desired image quality can be obtained with fewer post-reconstruction iterations.

[0072] Two examples of modified examples of embodiment 1 have been described above, however, the present invention is not limited to embodiment 1 and the modified examples, and the present invention also encompasses combinations of modified examples 1 and 2, addition of other functions, omission of some elements, or replacement with other elements having the same functions.

[0073] <Embodiments of Magnetic Resonance Imaging System> As shown in Fig. 13, the magnetic resonance imaging system of this embodiment is composed of an MRI apparatus 10 having an imaging unit 100 and a computer 200, and a data processing device 600. The data processing device 600 is connected to a UI unit 400 as an auxiliary device, and is connected to a database 500. Although the external storage device 300 shown in Fig. 1 is omitted in Fig. 13, the MRI apparatus 10 or the data processing device 600 may be provided with an external storage device 300 having the same functions as those of the first embodiment as an auxiliary device.

[0074] The configuration of the MRI apparatus 10 is similar to that of a general MRI apparatus, and among the functions of the computer 200 in the first embodiment, the functions of post-reconstruction and collection and analysis of user evaluations on the images are transferred to the data processing device 600. Although only one MRI apparatus 10 is shown here, a configuration in which a plurality of MRI apparatuses and the data processing device 600 are connected to process data (raw data and intermediate data) obtained by the plurality of MRI apparatuses may also be adopted.

[0075] The data processing device 600 comprises a post-reconstruction unit 610, an evaluation information collecting unit 620, and an evaluation information analyzing unit 630, and the functions of each of these units correspond to the functions of the image reconstruction unit 220, the image quality evaluation information collecting unit 231, the image quality evaluation result analyzing unit 232, and the recommended reconstruction condition determining unit 233 of embodiment 1, respectively. Therefore, a detailed description of the functions of each of these units will be omitted.

[0076] 3, the data processing device 600 accepts the start of processing from the MRI device 10 and starts steps S407 to S413. That is, first, post-reconstruction processing is started under the set reconstruction conditions (S407 to S409), and an image is output (S410). A user evaluation of this is accepted (S411), and this processing is repeated while changing the reconstruction conditions to collect evaluation information and store it in a database.

[0077] When the data processing device 600 receives the post-reconstruction processing, the data processing device 600 executes the evaluation information analysis processing of step S407 to S411 or directly executes the evaluation information analysis processing of step S412 to determine the recommended reconstruction conditions. The determined recommended reconstruction conditions may be presented to the UI unit 400 connected to the data processing device 600, or may be passed to the MRI device 10 and used for setting the imaging conditions in the MRI device 10 (S401).

[0078] According to the magnetic resonance imaging system of the present embodiment, it is possible to provide an additional function of presenting recommended reconstruction conditions to an existing MRI apparatus. In addition, by sharing a data processing device among multiple MRI apparatuses, the amount of stored data can be significantly increased, and the accuracy of evaluation data analysis can be improved.

[0079] FIG. 13 shows an example of functional division between the computer 200 and the data processing device 600 of the MRI apparatus 10. Various modifications are possible, such as transferring part of the computer 200 to the data processing device 600, or conversely transferring part of the functions of the data processing device 600 to the computer of the MRI apparatus 10, or both having the same functions overlapping each other, and these modifications are also encompassed by the present invention. [Explanation of symbols]

[0080] 10: MRI device, 100: imaging unit, 200: computer, 210: measurement control unit, 220: image reconstruction unit, 230: image quality evaluation control unit, 231: image quality evaluation information collection unit, 232: image quality evaluation result analysis unit, 233: recommended reconstruction condition determination unit, 240: reconstruction parameter input unit, 242: image quality evaluation information input unit, 243: recommended reconstruction condition display unit, 300: external storage device, 400: UI unit, 500: database, 600: data processing device

Claims

1. The present invention comprises an imaging unit that collects nuclear magnetic resonance signals generated by a subject, a calculation unit that generates a reconstructed image of the subject using raw data consisting of the nuclear magnetic resonance signals, and a reconstruction condition search unit that searches for recommended reconstruction conditions for the reconstructed image, The reconstruction condition search unit an image data acquisition unit that acquires image data generated by the calculation unit; a post-reconstruction unit that reconstructs an image under a reconstruction condition different from a reconstruction condition used when the image was reconstructed by the calculation unit, using the image data; an evaluation information collecting unit that presents the image reconstructed by the post-reconstruction unit, receives user evaluations on the image, and stores the evaluations in a database as evaluation data linking the user evaluations with reconstruction conditions; and an evaluation result analysis unit that analyzes the evaluation data stored in the database and determines recommended reconstruction conditions.

2. 2. The magnetic resonance imaging apparatus according to claim 1, The magnetic resonance imaging apparatus according to claim 1, wherein the image data acquisition unit acquires the raw data as the image data.

3. 2. The magnetic resonance imaging apparatus according to claim 1, The generation of the reconstructed image performed by the computing unit includes a multi-stage process, The magnetic resonance imaging apparatus according to claim 1, wherein the image data acquisition unit acquires, as the image data, intermediate data generated in any one of the multiple stages of processing.

4. 4. The magnetic resonance imaging apparatus according to claim 3, The multi-stage processing includes a conversion process of the raw data into an image space and a correction process for the image space data; The magnetic resonance imaging apparatus according to claim 1, wherein the image data acquisition unit acquires, as the image data, the image data after the conversion process.

5. 2. The magnetic resonance imaging apparatus according to claim 1, the reconstruction condition search unit further includes a simulation image generation unit that generates a simulation image using the recommended reconstruction conditions, A magnetic resonance imaging apparatus comprising: a display unit that displays the simulation image together with the recommended reconstruction conditions.

6. 2. The magnetic resonance imaging apparatus according to claim 1, The imaging device further includes a body movement determination unit that determines body movement during imaging, the image data acquisition unit acquires the body movement information determined by the body movement determination unit together with the image data; The magnetic resonance imaging apparatus according to claim 1, wherein the reconstruction condition search unit presents a reconstruction condition related to the body motion information as the recommended reconstruction condition.

7. 2. The magnetic resonance imaging apparatus according to claim 1, The magnetic resonance imaging apparatus according to claim 1, wherein the reconstruction condition search unit determines the recommended reconstruction conditions by statistical processing or machine learning using evaluation data stored in the database.

8. A method for presenting recommended reconstruction conditions to a user in magnetic resonance imaging for generating an image by reconstructing raw data consisting of nuclear magnetic resonance signals, comprising: a post-reconstruction step of reconstructing the image using the raw data or intermediate reconstruction data; receiving a user evaluation of the generated post-reconstruction image; accumulating evaluation data linking reconstruction conditions at the time of post-reconstruction with user evaluations of the post-reconstruction image; and analyzing the accumulated evaluation data to determine recommended reconstruction conditions.

9. The reconstruction condition search method according to claim 8, The method further includes a step of receiving information about body movement occurring during imaging; A reconstruction condition searching method, comprising presenting suggestions regarding body movements together with the recommended reconstruction conditions.

10. The reconstruction condition search method according to claim 8, A reconstruction condition search method, characterized in that the post-reconstruction step using intermediate data comprises a reconstruction step that omits the processing up to generating the intermediate data from raw data.

11. a magnetic resonance imaging device that collects nuclear magnetic resonance signals generated by a subject and generates a reconstructed image of the subject; and a data processing device that analyzes image data acquired by the magnetic resonance imaging device and searches for recommended reconstruction conditions, The data processing device includes: a post-reconstruction unit that uses the image data to reconstruct an image under reconstruction conditions different from those of the image reconstructed by the magnetic resonance imaging apparatus; an evaluation information collecting unit that presents the image reconstructed by the post-reconstruction unit, receives user evaluations on the image, and stores the evaluations in a database as evaluation data linking the user evaluations with reconstruction conditions; and an analysis unit that analyzes the evaluation data stored in the database and searches for recommended reconstruction conditions.

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