Magnetic resonance imaging apparatus and control method thereof

Abstract

To reduce time extension due to re-measurement when measuring data affected by body motion generated during inspection is re-measured.SOLUTION: To determine the necessity of remeasurement in consideration of the continuity of measurement data affected by body motion. Further, when re-measurement is performed, the measurement time (the number of phase encoding steps) of measurement data to be re-measured is taken into consideration, and measurement of a part of the other unmeasured measurement data is omitted.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to a magnetic resonance imaging apparatus (hereinafter referred to as an MRI apparatus), and particularly to processing of measurement data when a subject moves during an examination using an MRI apparatus. [Background technology]

[0002] In an MRI examination, a subject is placed in an imaging space where a static magnetic field is generated, and radio frequency magnetic field pulses and gradient magnetic field pulses are repeatedly applied according to a predetermined pulse sequence to perform imaging. If the subject moves during this imaging, motion artifacts will appear in the images using the measurement data obtained during imaging.

[0003] For this reason, conventionally, the movement of the subject during the examination is monitored, and if the measurement data being acquired is affected by body movement, the data (hereinafter referred to as body movement-affected data) is identified, and the body movement-affected data is deleted or corrected before image reconstruction, or if correction is not sufficient, the body movement-affected data is re-taken.

[0004] For example, Patent Document 1 describes a technique for monitoring patient movement using an image sensor installed in an imaging bore and taking necessary actions based on the location and level of the detected movement. This technique describes necessary actions such as pausing the scan until the movement stops and tagging data frames acquired during the movement.

[0005] Patent Document 2 also discloses a technology for analyzing the body movement of a subject and determining the need for subsequent processing, i.e., whether or not body movement correction and remeasurement are necessary, depending on the characteristics of the body movement. Patent Document 2 further describes that when excluding data affected by body movement in body movement correction, the thinning rate of the entire measurement data should be taken into consideration, and that restrictions should be placed on the data to be excluded depending on the region of k-space. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Patent No. 07242514 specification [Patent Document 2] Japanese Patent Application Publication No. 2023-022669 Summary of the Invention [Problem to be solved by the invention]

[0007] According to conventional techniques, such as the technique described in Patent Document 2, determining whether remeasurement is necessary based on the characteristics of body movement makes it possible to obtain images in which the effects of body movement are reduced without degrading image quality. However, there is a problem in that removing body movement-affected data and remeasurement while maintaining image quality increases imaging time. For example, body movement can take various forms, such as relatively continuous body movement and body movement that occurs frequently in a short period of time. However, if the decision to retake (remeasure) is made based only on the magnitude of body movement or the k-space position of the body movement-affected data, repeated remeasurements may be necessary, resulting in increased imaging time. Furthermore, if the decision to remeasure is made based on the proportion of body movement-affected data in k-space, the decision to remeasure is made after a certain proportion of measurement data has been collected, which may result in remeasurement of data that does not require remeasurement, inevitably increasing imaging time.

[0008] The objective of this embodiment is to provide a technology that can obtain images with reduced influence of body movement while minimizing the extension of imaging time that would otherwise be required to perform remeasurements to retake data affected by body movement. [Means for solving the problem]

[0009] The present invention provides criteria for determining whether remeasurement is necessary and the conditions for remeasurement, based on the position of the body motion influence data in k-space, particularly the position and continuity when the body motion influence data is in the high frequency range of k-space, and applies these criteria to the body motion influence data to determine subsequent processing, thereby optimizing processing and reducing the measurement time required for remeasurement.

[0010] That is, the MRI apparatus of the present invention comprises an imaging unit that acquires nuclear magnetic resonance signals of a subject, an image generation unit that reconstructs an image of the subject using k-space data consisting of the nuclear magnetic resonance signals acquired by the imaging unit, and a processor that includes a body motion processing unit that analyzes the subject's body motion during imaging and identifies body motion-affected data from the k-space data that is affected by the subject's body motion, and controls the imaging unit and the image generation unit. The processor determines whether to subject the body motion-affected data to body motion-corrected reconstruction or to remeasure it, depending on the position of the body motion-affected data in k-space and the number of consecutive data points, and controls the imaging unit to perform the remeasurement when it is determined that at least a portion of the body motion-affected data should be remeasured.

[0011] The method for controlling an MRI apparatus according to the present invention also includes the following steps. A step of identifying body motion effect data affected by body motion contained in k-space data collected by the MRI device; a step of determining whether or not remeasurement of the body motion effect data is necessary based on the position of the body motion effect data in k-space; a step of further determining whether or not remeasurement of the body motion effect data is necessary based on the number of consecutive data points of the body motion effect data when it is determined that remeasurement of at least a portion of the body motion effect data is necessary; and a step of setting conditions for remeasurement when it is determined that remeasurement of at least a portion of the body motion effect data is necessary. [Effects of the Invention]

[0012] According to the present invention, by taking into consideration the continuity of the body motion effect data, it is possible to determine whether or not remeasurement is necessary or adjust the conditions for remeasurement, thereby minimizing the number of data to be remeasured and shortening the measurement time while maintaining the image quality of the image after body motion correction. [Brief explanation of the drawings]

[0013] [Figure 1] Diagram showing the overall outline of an MRI device [Figure 2] Functional block diagram of the processor (body movement processing section) [Figure 3] Diagram explaining the regions of k-space data [Figure 4] Flowchart showing the processing flow of the processor [Figure 5] Schematic diagram of iterative reconstruction [Figure 6] Diagram explaining retaking of measurement data [Figure 7] 10A and 10B are diagrams showing two examples of data affected by body movement that occurred during k-space data measurement. [Figure 8] FIG. 10 is a diagram illustrating a threshold value related to the continuity of body movement effect data. [Figure 9] 10 is a flowchart showing the flow of processing by a processor according to the second embodiment. [Figure 10] FIG. 10 is a diagram for explaining the processing of the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0014] First, an outline of an MRI apparatus to which the present invention is applied will be described with reference to FIG. 1, the MRI apparatus 1 is broadly composed of an imaging unit 10, a processor 20 that performs various controls and calculations, and a user interface (UI) unit 30 that allows interaction between the imaging unit 10 and the processor 20 and the user. The main elements that make up the imaging unit 10 are housed in a gantry that provides the examination space.

[0015] The imaging unit 10 generates nuclear magnetic resonance in the nuclei (usually protons) of atoms constituting the tissue of the subject, and collects nuclear magnetic resonance signals (NMR signals) generated from the subject. Hereinafter, the nuclear magnetic resonance signals are also simply referred to as measurement signals or echo signals.

[0016] The imaging unit 10 has a configuration similar to that of a known MRI apparatus, and includes a static magnetic field magnet 101 that generates a uniform magnetic field (static magnetic field) in an examination space in which a subject 50 is placed, a gradient magnetic field coil 102 that applies a gradient magnetic field to the static magnetic field, an RF transmission coil 103 that applies a radio frequency magnetic field that excites the nuclei of atoms that constitute the subject's tissue, and an RF reception coil 104 that receives an NMR signal generated by the subject. The gradient magnetic field coil 102, the RF transmission coil 103, and the RF reception coil 104 are connected to a gradient magnetic field power supply 105, a transmitter 106, and a receiver 107, respectively. The operations of the gradient magnetic field power supply 105, the transmitter 106, and the receiver 107 are controlled by a sequencer 108. The sequencer 108 determines a pulse sequence for each scan using a set pulse sequence type and imaging conditions such as imaging parameters, and controls each component of the imaging unit 10 to operate in accordance with the determined pulse sequence and collect echo signals (k-space data) required for image reconstruction. The functions and operations of each unit when the imaging unit 10 acquires k-space data are the same as those of a general MRI apparatus, and therefore detailed description thereof will be omitted here.

[0017] The static magnetic field magnet 101, gradient magnetic field coil 102, and RF transmitting coil 103 are housed in the gantry, and the subject 50 has an RF receiving coil 104 attached to the area to be examined and is positioned in the examination space within the gantry while lying on a bed device 40.

[0018] The processor 20 is a device that controls and performs calculations for the device, and can be configured with a known processing device such as a computer with a CPU and memory, a programmable IC, or a combination of these. In the case of a computer, for example, processing by the processor is realized by the CPU loading a program that achieves each control and calculation function. Also, all of the processor functions can be realized by a single processor, or each function can be realized by combining one or more processors. In Figure 1, one processor 20 is shown to represent one or more processors, and individual functions realized by one or more processors 20 are shown.

[0019] 1, the processor 20 includes an imaging control unit 210 that controls the operation of the imaging unit 10, an image generation unit 220 that generates an image of the subject using echo signals collected by the imaging unit 10, a body movement processing unit 230 that performs processing related to body movements of the subject 50 during the examination, and a display control unit 250 that controls a GUI for displaying the images generated by the image generation unit 220 and interacting with the user. Note that Fig. 1 illustrates typical functions of the processor 20 of this embodiment, and each of these does not necessarily correspond to an individual processor or processing unit. There are also cases where one processor or processing unit realizes the functions of multiple functional units, or where multiple processors or multiple processing units realize one function.

[0020] The imaging control unit 210 controls the imaging unit 10 via a sequencer 108 that operates each element of the imaging unit 10 according to a predetermined pulse sequence. The sequencer 108 operates each component of the imaging unit 10 based on imaging conditions, such as a pulse sequence and scan parameters, determined by an examination flow or set by a user. When a body motion processing unit 230 (described later) collects body motion information from echo signals for body motion detection (navigator echoes), the imaging control unit 210 executes a sequence for collecting navigator echoes together with or incorporated into an imaging pulse sequence. Furthermore, the imaging control unit 210 controls the stopping and resumption of imaging according to the body motion analyzed by the body motion processing unit 230, and also controls remeasurement to recapture part of the k-space data affected by the body motion.

[0021] The image generation unit 220 performs calculations necessary for image reconstruction, such as Fourier transform and sequential calculations, on the k-space data collected by the imaging unit 10, and also performs calculations such as correction on the k-space data before reconstruction or the image after reconstruction. In this embodiment, image reconstruction is performed with body movement corrected (body movement corrected reconstruction) in accordance with the body movement analyzed by the body movement processing unit 230. Furthermore, when part of the k-space data is remeasured by the imaging unit 10, image reconstruction may be performed by combining the k-space data obtained by the remeasurement with the k-space data obtained before the remeasurement.

[0022] The body motion processor 230 collects and processes body motion information generated by the subject 50 during the examination, such as the magnitude and duration of the body motion, and particularly information regarding the number of consecutive data points. The body motion information is linked to the ongoing scan (imaging) to determine whether body motion correction or remeasurement is necessary. The body motion information can be acquired from a monitoring camera 80 for monitoring the movement of the subject 50 and a body motion detection means, such as a navigator echo, which detects the subject's movement. While one monitoring camera 80 is shown as a representative example in FIG. 1 , one or more cameras 80 are installed near or inside the gantry, acquire images of the examination space, and send them to the processor 20 (body motion processor 230). As described above, the navigator echo is a nuclear magnetic resonance signal collected by the imaging unit 10 to detect the subject's movement, separate from the nuclear magnetic resonance signal (echo signal) used to generate an image of the subject. The body motion processor 230 extracts the subject's movement during imaging by analyzing the navigator echo acquired in time series.

[0023] The body motion processor 230 determines whether or not body motion correction or remeasurement is necessary based on the acquired body motion information. A functional block diagram realizing the functions of the body motion processor 230 is shown in FIG. 2. As shown in the figure, the body motion processor 230 may include a body motion-affected data identifying unit 231, a k-space region identifying unit 232, and a processing determination unit 233. The body motion-affected data identifying unit 231 determines that the measurement data is affected by body motion (body motion-affected data) based on the body motion information during measurement, such as the magnitude of the body motion, and identifies the measurement data as body motion-affected data. Body motion-affected data is a collection of one or more echo signals collected while a single body motion occurs. For example, if body motion exceeding a predetermined threshold magnitude occurs discontinuously, each body motion is identified as body motion-affected data.

[0024] The k-space region specifying unit 232 divides the k-space data into multiple regions to specify the position of the body motion effect data in k-space by the region of k-space. The region division is not limited to this, but may be divided into three regions, for example, a low frequency region sandwiching the center of the k-space and two high frequencies (upper high frequency region and lower high frequency region) outside the low frequency region, as shown in FIG. 3, or each of these may be further divided into two or more regions. In the former case, for example, the low frequency region may be 50% of the k-space, and the two high frequencies may each be 25% of the k-space. Such region division may be set by a predetermined ratio in advance, or may be set or changed by the user. When the region division is set on the device side, the extent to which image quality will deteriorate when data from a certain region is missing may be estimated in advance using simulation or AI, and the setting may be based on this.

[0025] The processing determination unit 233 determines which region the body motion effect data belongs to based on the phase encoding information linked to the body motion effect data and the continuity (number of consecutive data points) of the body motion effect data in accordance with this region division, and determines whether remeasurement is necessary based on the region and continuity. In this case, the determination is made using a threshold value for the continuity. A predetermined value may be used as the threshold value, or a preset value may be adjusted based on the distribution of the body motion effect data in k-space. The determination of data continuity using a threshold value and its adjustment will be described in detail in the following embodiment.

[0026] The display control unit 250 displays the images generated by the image generation unit 220 and their associated information on a display device in a predetermined display format. The display control unit 250 further performs processes such as displaying a GUI on the display device for the user to input various conditions and settings related to the operation of the MRI apparatus 1, such as imaging, image generation (including correction), and display, accepting user settings, and passing them to related functional units. The UI unit 30 includes a display device and an input device as means for communication between the processor 20 and the user, and these are connected to the processor 20.

[0027] Next, the flow of imaging operations of the MRI apparatus 1 in the above configuration will be described with reference to FIG.

[0028] The subject 50 is placed in the examination space, and imaging is started (S1). Specific imaging conditions, i.e., the pulse sequence and scan parameters (number of slices, FOV, TE, TR, R factor, etc.) used for imaging are not particularly limited, and imaging is performed by setting various known conditions using known setting methods.

[0029] Before or simultaneously with the start of imaging, the body motion processor 230 monitors the subject's motion and collects body motion information (S2). The subject's motion can be obtained, for example, by collecting navigator echoes for monitoring the subject's motion separately from echo signals for image reconstruction, and analyzing changes in the profile obtained by Fourier transforming the navigator echoes in the direction of the motion to be monitored, or by analyzing changes in the navigator echoes themselves. Various pulse sequences for collecting navigator echoes and accompanying imaging sequences are known, so a description of specific sequences will be omitted here.

[0030] Instead of using navigator echoes, it is also possible to obtain motion from images from a surveillance camera installed inside or near the gantry of the MRI device 1 or signals from a biosignal monitor attached to the subject, or to use both. The body motion processing unit 230 analyzes these images and signals and collects body motion information such as the magnitude of body motion, information about the time of body motion occurrence, and the type of body motion. Known methods can be used to obtain motion information using surveillance camera images, such as calculating the movement vector of each pixel between frame images of the surveillance camera and obtaining motion information using optical flow calculations. Furthermore, if respiratory motion or heartbeat is obtained as a biosignal, it is also possible to use these signals to identify body motion that affects the image, excluding periodic motion.

[0031] As a result of the analysis by the body motion processing unit 230 (S3), if no body motion that affects the image, such as sudden motion or positional deviation excluding relatively small periodic motions such as respiratory motion and heartbeat, is detected, once the measurement data (k-space data) required to reconstruct the image is collected, the image generation unit 220 uses the collected k-space data to reconstruct the image using a known image reconstruction method such as Fourier transform or PI calculation (S4).

[0032] If the analysis by the body motion processor 230 determines that body motion occurred during the acquisition of k-space data (S3), the body motion processor 230 (body motion-affected data identifying unit 231, k-space region identifying unit 232) identifies measurement data affected by body motion (body motion-affected data) based on the time of body motion occurrence and identifies its k-space region. Next, the body motion processor 230 (processing determination unit 233) determines whether to delete or correct the identified body motion-affected data and perform body motion-corrected reconstruction, or to remeasure (S5, S6). The determination of whether to remeasure depends, for example, on whether the body motion-affected data is k-space low-frequency data or k-space high-frequency data. If it is k-space low-frequency data, remeasurement is performed (S5), and if it is k-space high-frequency data, the process proceeds to the next determination step (S6).

[0033] Furthermore, the body motion processor 230 determines whether to remeasure the body motion-affected data based on its position and continuity in k-space, or to use the data for body motion-corrected reconstruction without remeasurement (S6). A preset threshold value is used for the continuity, or a threshold value adjusted according to the position in k-space. If the continuity is equal to or greater than the threshold value, remeasurement is performed, and if it is less than the threshold value, measurement is continued without remeasurement. Specific decisions for each case will be described later.

[0034] When motion correction is performed using k-space data collected without retaking the image, the image generator 220 generates a motion-corrected image using a predetermined method (S7). As a motion correction method, known methods can be used, such as zero-filling, which deletes data to be corrected and fills it with zeros, half-scan reconstruction, reconstruction using data estimation utilizing Hermitian symmetry of k-space, and iterative reconstruction using k-space data after zero-filling as shown in FIG.

[0035] If it is determined that motion-corrected reconstruction using motion-affected data is not possible or that remeasurement is necessary, the imaging control unit 210 controls the imaging unit 10 to perform remeasurement. That is, the imaging unit 10 stores k-space data acquired up until the occurrence of motion in memory, and remeasures k-space data from the time point at which motion occurred (S8). When the measurement data necessary for image reconstruction is collected by the remeasurement, the image generation unit 220 generates an image using the measurement data before remeasurement stored in memory and the data collected after remeasurement (S8). Note that the remeasurement may be performed automatically according to the result of judgment step S6, or may be configured to start upon user approval or selection of remeasurement.

[0036] The image generated by the image generation unit 220 is displayed on the display device of the UI unit 30 via the display control unit 250 (S9). The image data may also be sent to an external storage device, database, or the like.

[0037] As described above, the MRI apparatus of this embodiment monitors the body movement of the subject during an examination, identifies image-influencing data that is measurement data acquired when body movement occurs and that has a large influence on the image from the body movement, and determines whether remeasurement is necessary based on the position in k-space of the image-influencing data and the continuity of the data in k-space. This reduces the frequency of remeasurement and prevents remeasurement of measurement data that does not actually need to be remeasured, thereby preventing an increase in imaging time.

[0038] Hereinafter, specific embodiments of the processing performed by the body movement processing unit 230 will be described for each of various cases of body movement that occurs during data collection.

[0039] <Embodiment 1> In this embodiment, if there is body motion affected data in the low frequency range of k-space, re-measurement is performed, and if there is body motion affected data in the high frequency range of k-space, the necessity of re-measurement is determined based on the continuity of the data. The operation of the processing determination unit 233 of this embodiment will be described below with reference to the flowchart of Fig. 4 again. In this embodiment, the case where the sampling order is sequential, acquiring data from one high frequency range of k-space via the low frequency range to the other high frequency range of k-space, will be described as an example.

[0040] In this embodiment, the processing determination unit 233 first determines in which region of k-space the body motion affected data identified by the body motion affected data identification unit 231 is located (S5). The region of k-space is assumed to be divided into high and low frequencies, as shown in Division Example 1 of FIG. 3, for example. In this determination, if the body motion affected data is low frequency data, the low frequency data is re-captured. That is, as shown in FIG. 6, re-measurement is started from the phase encode identified as the body motion affected data of the low frequency data, and the subsequent phase encode data, i.e., data from the low frequency to the high frequency that has not been measured up to that point, is measured. 6, body movement influence data exists only in the low frequency range, but re-shooting is also performed when body movement influence data exists from the high frequency range to the low frequency range. In other words, when body movement influence data exists in the low frequency range, it is determined in the decision steps (S5, S6) that re-measurement is required.

[0041] On the other hand, as shown in the upper part of Fig. 7, if the body motion affected data is high frequency data, a further decision is made as to whether or not re-imaging is necessary based on the number of high frequency data and the number of consecutive data (S6). This second decision is made by setting a predetermined threshold value TH for the number of consecutive data, and if the number of consecutive data is equal to or greater than TH, the body motion affected data is re-imaging, and if it is less than TH, re-imaging is not performed. The number of consecutive data means the number of consecutive data in k space when the measurement data is arranged in k space, and in the case of sequential order, the measurement order is the arrangement order in k space, and there are two orders: from high frequency to low frequency, and from low frequency to high frequency.

[0042] Here, body movement effect data refers to a set of data specified corresponding to one body movement, and if body movement occurs multiple times discontinuously between the echo measurement and the body movement analysis, there may be multiple body movement effect data, as shown in the lower part of Fig. 7. In that case, the body movement processing unit 230 judges whether the number of consecutive pieces of body movement effect data generated within the time interval (monitoring window) during which it monitors body movement is greater than or equal to a threshold value.

[0043] If the number is above the threshold, it means that there is a continuous stretch of data that cannot be used when performing motion-corrected reconstruction, and even if the motion-affected data is zero-filled or estimated and reconstructed using sequential calculations, the image quality will deteriorate because there is little information in that area. Therefore, in the second judgment step, to prevent such image degradation, it is determined that re-imaging (re-measurement) is necessary if the number of continuous data is above the threshold.

[0044] At this time, the processing determination unit 233 may adjust the threshold used in the second determination step S6 depending on the position in k-space of the body motion effect data. For example, in the example at the bottom of Fig. 7 where multiple body motion effect data are identified, the threshold for the number of consecutive data may be set to be different for body motion effect data located on the higher frequency side and for body motion effect data located closer to the low frequency side, with the threshold for the former being larger than the threshold for the latter, i.e., the closer to the low frequency side the threshold is, the smaller the threshold is, so that even a small number of consecutive data points requires re-imaging.

[0045] The threshold may be changed stepwise for each region when the high frequency range is divided into smaller regions as shown in division example 2 in Fig. 3. Alternatively, the threshold may be changed linearly (as a linear function) or nonlinearly (as an exponential function, etc.) with respect to the phase encoding amount as shown in Fig. 8. That is, the proportion of continuous data for determining whether to retake images at a k-space position in the phase direction (simply referred to as a k-space position) is expressed by the following equation when measuring from the low frequency range to the high frequency range.

[0046] [Percentage of continuous data for retake determination (%)] = [(threshold of k-space position B - threshold of k-space position A)] / (k-space position Bk-space position A)] × (k-space position when body movement occurred) When measuring from high to low frequencies, the "k-space position when body movement occurs" becomes the "k-space position when body movement ends." In other words, the proportion of continuous data determined by the threshold is determined based on the position of the lowest frequency data in the body movement-affected data.

[0047] In this way, by increasing the threshold for determining the continuity of body motion affected data as the body motion affected data moves away from the low frequency range, a stricter threshold (smaller threshold) is used to determine whether to retake the body motion affected data that includes data in a range close to the low frequency range, preventing the loss of information on data that affects the contrast of the image. Also, for body motion affected data composed of data on the higher frequency range, body motion correction is performed because the data has little effect on the image, and by not retaking the image, an extension of the imaging time is prevented.

[0048] Although it is not essential to adjust the threshold based on the position of the body motion effect data, by adjusting the threshold according to the position of the body motion effect data in k-space, it is possible to reduce the extension of imaging time while maintaining image quality.

[0049] According to this embodiment, in cases where body motion effect data exists in the high frequency range of k-space, the need for remeasurement is determined based on the continuity of the body motion effect data, thereby minimizing the frequency of remeasurement and the amount of data to be remeasured.

[0050] In the above embodiment, if body motion influence data exists in the low frequency range, it is determined that remeasurement is necessary, but it is also possible to set a threshold value for the number of consecutive body motion influence data in the low frequency range that is smaller than that in the high frequency range, and not retake the image. In this case, a gradient may also be set for the threshold value in the low frequency range, so that the threshold value is set lower as the value approaches 0 encoding.

[0051] <Embodiment 2> In this embodiment, when body motion affected data is in the low frequency range of k-space and the low frequency data is re-acquired, the extension of the measurement time including the re-measurement is reduced by limiting the measurement data to be re-measured. The processing flow of the body motion processor 230 in this embodiment will be described with reference to Fig. 9. In Fig. 9, the same processes as in Fig. 4 are designated by the same reference numerals, and redundant explanations will be omitted.

[0052] FIG. 10 shows an example of a case where this embodiment is applied. Here, as in the first embodiment, the sampling order will be described using sequential ordering as an example, but is not limited thereto. As shown in FIG. 10, assume that body movement occurs during measurement of low-frequency data when measurements (scans) are performed sequentially from one high frequency band in k-space through the origin to the other high frequency band. The body movement processor 230 determines whether the data measured during body movement is body movement-affected data based on the location where the body movement occurred and the magnitude of the body movement (S3). If the data is body movement-affected data, it determines which region of k-space the data belongs to (S5). If the body movement-affected data is low-frequency data, remeasurement is performed. In the remeasurement, the remaining k-space data (part of the low-frequency data) excluding the high-frequency data that has already been measured and the low-frequency data measured when no body movement has occurred, as well as unmeasured high-frequency data, are measured.

[0053] At this time, the processing determination unit 233 omits acquisition of high-frequency data for a period equivalent to the acquisition period (Δt) of the body motion influence data to be retaken (S10). That is, the remaining high-frequency data is measured by omitting a number of phase encoding steps equivalent to the number of phase encoding steps of the low-frequency data to be remeasured. The high-frequency data to be omitted is preferably data located on the highest frequency side. Alternatively, the number of phase encoding steps to be omitted may be distributed, and the high-frequency data may be thinned out for measurement.

[0054] The number of phase encoding steps for which measurement is omitted may be the same as the number of phase encoding steps for the low-frequency data, or it may be more or less than that, as long as body motion correction can be accommodated even if the steps are omitted. By omitting as many as possible, it is possible to compensate for the time extension due to re-measurement and shorten the measurement time.

[0055] Finally, when all k-space data has been collected, image reconstruction or motion-corrected reconstruction is performed using the k-space data (S8), as in the first embodiment.

[0056] According to this embodiment, if remeasurement is necessary, the time required to remeasure the body movement influence data that was the subject of remeasurement can be canceled by omitting measurement of some of the high-frequency data, thereby preventing an extension of the measurement time, including remeasurement.

[0057] 10 illustrates an example in which low-frequency data is remeasured, but this embodiment can also be applied to a case in which high-frequency data is re-acquired before measuring low-frequency data. In other words, the number of phase encoding steps equivalent to the number of phase encoding steps of the high-frequency data that has been re-acquired may be omitted when measuring the unmeasured high-frequency data.

[0058] The above describes embodiments of the processing performed by the body movement processing unit of the MRI apparatus of the present invention. However, the present invention is characterized in that it controls processing decisions and subsequent remeasurement by taking into consideration the continuity of body movement influence data, and is not limited to these embodiments, but can be modified to suit various ways in which body movement occurs. [Explanation of symbols]

[0059] 10: imaging unit, 20: processor, 210: imaging control unit, 220: image generation unit, 230: body movement processing unit, 231: body movement influence data identification unit, 232: k-space region identification unit, 233: processing determination unit, 250: display control unit

Claims

1. an imaging unit that collects nuclear magnetic resonance signals of a subject; an image generating unit that reconstructs an image of the subject using k-space data consisting of the nuclear magnetic resonance signals collected by the imaging unit; and a processor that includes a body movement processing unit that analyzes body movement of the subject during imaging and identifies body movement-affected data of the k-space data that is affected by the body movement of the subject, and controls the imaging unit and the image generating unit; The processor determines whether to subject the body motion effect data to body motion corrected reconstruction or to remeasure it, depending on the position of the body motion effect data in k-space and the number of consecutive data, and when it determines that at least a portion of the body motion effect data should be remeasured, controls the imaging unit to perform the remeasurement.

2. 2. The magnetic resonance imaging apparatus according to claim 1, The processor divides k-space into at least two regions including a low-frequency region and a high-frequency region, and when all of the body motion influence data are data in the low-frequency region, controls the imaging unit to perform remeasurement regardless of the number of consecutive data, and when the body motion influence data are data in the high-frequency region, determines whether or not remeasurement is necessary based on a threshold value set for the number of consecutive data.

3. 2. The magnetic resonance imaging apparatus according to claim 1, The magnetic resonance imaging apparatus is characterized in that the processor controls the imaging unit to re-measure the body motion effect data when the number of consecutive data pieces of the body motion effect data is equal to or greater than a predetermined threshold, regardless of the position of the consecutively collected data in k-space.

4. 4. The magnetic resonance imaging apparatus according to claim 3, the processor sets the threshold to a different value for each of the regions of the k-space divided into a plurality of regions; A magnetic resonance imaging apparatus characterized in that a decision is made as to whether or not remeasurement is necessary using a threshold value set for the region of k-space to which the continuously acquired data belongs.

5. 4. The magnetic resonance imaging apparatus according to claim 3, a threshold value that changes from a low frequency region to a high frequency region of k-space as the threshold value, and a threshold value according to a position in k-space of the continuously collected data, to determine whether or not remeasurement is necessary.

6. 2. The magnetic resonance imaging apparatus according to claim 1, When the number of consecutive data points of the body motion influence data is less than a preset threshold, the processor determines that remeasurement of the body motion influence data is unnecessary; The magnetic resonance imaging apparatus is characterized in that the image generating unit performs motion-corrected reconstruction by correcting or excluding the motion-affected data to generate an image.

7. 2. The magnetic resonance imaging apparatus according to claim 1, A magnetic resonance imaging apparatus characterized in that, when at least a portion of the body motion effect data and unmeasured data are remeasured, the processor controls the imaging unit to omit measurement of at least a portion of the unmeasured data.

8. 8. The magnetic resonance imaging apparatus according to claim 7, The magnetic resonance imaging apparatus is characterized in that the processor sets the number of unmeasured data for which measurement is omitted to be equal to the number of body motion effect data.

9. 8. The magnetic resonance imaging apparatus according to claim 7, The magnetic resonance imaging apparatus is characterized in that the processor controls the imaging unit so as to perform measurements by thinning out the unmeasured data.

10. 1. A method for controlling a magnetic resonance imaging device, comprising: Identifying body movement-affected data that is affected by body movement and is included in k-space data acquired by the magnetic resonance imaging apparatus; determining whether or not remeasurement of the body motion effect data is necessary based on the position of the body motion effect data in k-space; if it is determined that remeasurement is not necessary, further determining whether or not remeasurement of the body movement influence data is necessary based on the number of consecutive data of the body movement influence data; a step of setting a condition for remeasurement when it is determined that remeasurement of at least a part of the body motion effect data is necessary; A method for controlling a magnetic resonance imaging apparatus comprising:

11. 11. A method for controlling a magnetic resonance imaging apparatus according to claim 10, comprising: The step of setting conditions for remeasurement includes: A control method for a magnetic resonance imaging apparatus, comprising, when the remeasurement includes measurement of unmeasured data among the k-space data, setting a condition for omitting measurement of part of the unmeasured data.

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