Image processing device and image processing method

Abstract

An image processing device and an image processing method, the image processing device comprising: an imaging k-space data acquisition unit that acquires a plurality of imaging k-space data; a template k-space data acquisition unit that acquires a plurality of template k-space data with opposite readout gradient polarity at echo times corresponding to echo times at which each of the plurality of imaging k-space data is acquired; a target k-space data generation unit that generates target k-space data based on the template k-space data and the imaging k-space data acquired at the same echo time; a kernel calculation unit that calculates a plurality of kernels for correcting a phase error of at least one imaging k-space data or generating unsampled data in at least one imaging k-space data based on the target k-space data and the imaging k-space data; a synthesized k-space data generation unit that synthesizes the plurality of kernels with the imaging k-space data to generate synthesized k-space data; and an image generation unit that generates an image of an examination site using the synthesized k-space data.

Description

Technical Field

[0001] The invention relates to an image processing device and an image processing method for performing signal acquisition using a bipolar multi-echo acquisition method. Background Art

[0002] Magnetic resonance imaging (MRI) is sometimes used to quantitatively determine fat in an examination area of ​​a subject. MRI-based fat quantification methods can provide quantitative and spatial information on fat accumulation in the human body for diagnosis in a non-invasive manner.

[0003] MRI-based fat quantification methods require long scanning times, so bipolar acquisition technology and parallel imaging technology are usually used to shorten scanning time.

[0004] In bipolar acquisition techniques, data is collected by applying positive and negative gradients. Eddy currents in the system can cause phase errors in the acquired data. Correcting this phase error typically involves inferring a one-dimensional or two-dimensional phase error model from scans of templates with or without encoding, respectively. Correction is then performed based on these models.

[0005] In parallel imaging technology, multi-channel coils are used and the data is undersampled, and methods including generalized auto calibrating partially parallel acquisition (GRAPPA) and sensitivity encoding (SENSE) are used to reconstruct images.

[0006] A more sophisticated parallel imaging reconstruction method is the bipolar GRAPPA method, which is used to synthesize missing k-space data in echo planar imaging (EPI) while simultaneously correcting for the inherent phase errors caused by reversed readout gradient polarity. The bipolar GRAPPA method demonstrates superior image quality in regions where high-order EPI phase errors typically occur.

[0007] However, in bipolar acquisition techniques and parallel imaging, one-dimensional phase error correction cannot completely eliminate phase errors, especially phase errors along the phase encoding (PE) direction. Two-dimensional phase error correction is performed in image space and requires dewarping from the phase error map, which is often difficult and can fail in certain areas with high phase warping. In addition, undersampled images must first be expanded using SENSE or GRAPPA, and any motion artifacts will degrade the quality of phase error correction.

[0008] Furthermore, parallel imaging reconstruction methods like SENSE require acquiring separate mapping scans, which can be affected by respiratory motion when imaging the abdomen, introducing errors in image reconstruction. Summary of the Invention

[0009] The present invention provides an image processing device and an image processing method which can remove the phase error of acquired data and reconstruct unsampled data in a bipolar multi-echo acquisition mode.

[0010] The image processing device of the present invention is used to image an examination part of a subject in a bipolar multi-echo acquisition, and comprises: an imaging k-space data acquisition unit for acquiring a plurality of imaging k-space data by performing a first bipolar multi-echo acquisition on the examination part; a template k-space data acquisition unit for performing a second bipolar multi-echo acquisition on the examination part, acquiring a plurality of template k-space data at an echo time corresponding to each echo time for acquiring the plurality of imaging k-space data using a readout gradient polarity opposite to that of the first bipolar multi-echo acquisition; and a target k-space data generation unit for generating a target k-space data based on the template k-space data acquired at the same echo time. and imaging k-space data to generate target k-space data without phase error of the imaging k-space data; a kernel calculation unit calculates a plurality of kernels for correcting the phase error of at least one imaging k-space data including the imaging k-space data or generating unsampled data in the at least one imaging k-space data based on the target k-space data and the imaging k-space data; a synthetic k-space data generation unit synthesizes the plurality of kernels with each of the at least one imaging k-space data to generate synthetic k-space data; and an image generation unit generates an image of the examination part using the synthetic k-space data.

[0011] The imaging k-space data may be data obtained by fully sampling the central portion of the k-space and undersampling the peripheral portion of the k-space, and the template k-space data may be data obtained by fully sampling the central portion of the k-space.

[0012] The target k-space data generating unit may generate the target k-space data by combining the template k-space data with k-space data in a central portion of the imaging k-space data acquired at the same echo time.

[0013] It can also be formed that the above-mentioned kernel calculation unit calculates multiple kernels for correcting the phase error of the isodirectional imaging k-space data having the same readout direction as the imaging k-space data or generating unsampled data in the isodirectional imaging k-space data based on the above-mentioned target k-space data of the above-mentioned imaging k-space data and the imaging k-space data, and the above-mentioned synthetic k-space data generation unit synthesizes the above-mentioned multiple kernels with the above-mentioned isodirectional imaging k-space data to generate synthetic k-space data.

[0014] It can also be formed so that the above-mentioned multiple kernels are coefficient matrices, and the above-mentioned multiple kernels include: a first kernel for correcting the phase of the k-space data in the peripheral area of ​​the imaging k-space data; a second kernel for correcting the phase of the k-space data in the central area of ​​the imaging k-space data; and a third kernel for generating unsampled data in the peripheral area of ​​the imaging k-space data.

[0015] It can also be formed that the above-mentioned isotropic imaging k-space data is multiple, the above-mentioned kernel calculation unit calculates the above-mentioned first kernel, the above-mentioned second kernel and the above-mentioned third kernel for each of the above-mentioned isotropic imaging k-space data, and averages or weighted averages the calculated multiple first kernels to generate a first average kernel, averages or weighted averages the calculated multiple second kernels to generate a second average kernel, and averages or weighted averages the calculated multiple third kernels to generate a third average kernel, and the above-mentioned synthetic k-space data generation unit synthesizes the above-mentioned first average kernel, the above-mentioned second average kernel and the above-mentioned third average kernel with each of the above-mentioned isotropic imaging k-space data to generate synthetic k-space data.

[0016] The image processing method of the present invention is used to image an examination part of a subject in a bipolar multi-echo acquisition, and comprises: an imaging k-space data acquisition step, in which a plurality of imaging k-space data are acquired by performing a first bipolar multi-echo acquisition on the examination part; a template k-space data acquisition step, in which a second bipolar multi-echo acquisition is performed on the examination part, and a plurality of template k-space data are acquired at an echo time corresponding to each echo time for acquiring the plurality of imaging k-space data, using a readout gradient polarity opposite to that of the first bipolar multi-echo acquisition; a target k-space data generation step, in which a target k-space data is generated based on the template k-space data acquired at the same echo time. and imaging k-space data to generate target k-space data without phase error of the imaging k-space data; a kernel calculation step, calculating a plurality of kernels for correcting the phase error of at least one imaging k-space data including the imaging k-space data or generating unsampled data in the at least one imaging k-space data based on the target k-space data and the imaging k-space data; a synthetic k-space data generation step, synthesizing the plurality of kernels with each of the at least one imaging k-space data to generate synthetic k-space data; an image generation step, using the synthetic k-space data to generate an image of the examination part.

[0017] The imaging k-space data may be data obtained by fully sampling the central portion of the k-space and undersampling the peripheral portion of the k-space, and the template k-space data may be data obtained by fully sampling the central portion of the k-space.

[0018] In the target k-space data generating step, the target k-space data may be generated by combining the template k-space data and the k-space data of the central portion of the imaging k-space data acquired at the same echo time.

[0019] It can also be formed as follows: in the above-mentioned kernel calculation step, multiple kernels for correcting the phase error of the isodirectional imaging k-space data having the same readout direction as the imaging k-space data or generating unsampled data in the isodirectional imaging k-space data are calculated based on the above-mentioned target k-space data of the above-mentioned imaging k-space data and the imaging k-space data; in the above-mentioned synthetic k-space data generation step, the above-mentioned multiple kernels are synthesized with the above-mentioned isodirectional imaging k-space data to generate synthetic k-space data.

[0020] It can also be formed so that the above-mentioned multiple kernels are coefficient matrices, and the above-mentioned multiple kernels include: a first kernel for correcting the phase of the k-space data in the peripheral area of ​​the imaging k-space data; a second kernel for correcting the phase of the k-space data in the central area of ​​the imaging k-space data; and a third kernel for generating unsampled data in the peripheral area of ​​the imaging k-space data.

[0021] It can also be formed that the above-mentioned isotropic imaging k-space data is multiple, and in the above-mentioned kernel calculation step, the above-mentioned first kernel, the above-mentioned second kernel and the above-mentioned third kernel are respectively calculated for each of the above-mentioned isotropic imaging k-space data, and the calculated multiple first kernels are averaged or weighted averaged to generate a first average kernel, the calculated multiple second kernels are averaged or weighted averaged to generate a second average kernel, and the calculated multiple third kernels are averaged or weighted averaged to generate a third average kernel. In the above-mentioned synthetic k-space data generation step, the above-mentioned first average kernel, the above-mentioned second average kernel and the above-mentioned third average kernel are synthesized with each of the above-mentioned isotropic imaging k-space data to generate synthetic k-space data.

[0022] Effects of the Invention

[0023] According to the image processing device and the image processing method of the present invention, in a bipolar multi-echo acquisition mode, the phase error of acquired data can be removed and unsampled data can be reconstructed. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 This is a block diagram showing the basic structure of the magnetic resonance imaging apparatus of the present invention.

[0025] Figure 2 It is a structural block diagram of the image processing device of the present invention.

[0026] Figure 3 A map is generated for generating a plurality of imaging k-space data and corresponding template k-space data.

[0027] Figure 4 This is a map for generating target k-space data.

[0028] Figure 5 Here is a graph that generates 3 kernels.

[0029] Figure 6 This is a diagram of synthetic k-space data generated using three kernels.

[0030] Figure 7 This is a graph that generates an average kernel for multiple isotropic imaging k-space data.

[0031] Figure 8 is a flowchart of the image processing method of the present invention. DETAILED DESCRIPTION

[0032] Below, based on Figures 1 to 4 The magnetic resonance imaging apparatus 1 of the present invention will be described.

[0033] Figure 1This is a block diagram showing the basic structure of the magnetic resonance imaging apparatus 1 of the present invention. The following describes the various components of the magnetic resonance imaging apparatus 1. The static magnetic field magnet 10 generates a static magnetic field in the imaging space where the subject is located. For example, the static magnetic field magnet 10 is formed of a superconducting magnet or a permanent magnet.

[0034] The gradient magnetic field coils 20 generate gradient magnetic fields. For example, the gradient magnetic field coils include X-coils, Y-coils, and Z-coils corresponding to the mutually orthogonal X-axis, Y-axis, and Z-axis, respectively. The X-coils, Y-coils, and Z-coils generate gradient magnetic fields along the respective axes using current supplied by the gradient magnetic field power supply 30. The Z-axis is defined along the magnetic flux of the static magnetic field generated by the static magnetic field magnet 10. Furthermore, the X-axis is defined along the horizontal direction orthogonal to the Z-axis. The Y-axis is defined along a direction orthogonal to both the Z-axis and the X-axis.

[0035] The gradient magnetic field power supply 30 supplies current to the gradient magnetic field coil 20. The gradient magnetic field power supply 30 supplies current to the gradient magnetic field coil 20, so that the gradient magnetic field coil 20 can generate a gradient magnetic field.

[0036] The RF (Radio Frequency) coil 40 applies a high-frequency magnetic field to the subject placed in the imaging space and receives NMR (Nuclear Magnetic Resonance) signals generated from the subject. The high-frequency magnetic field is sometimes also called an RF pulse. The RF coil 40 includes a whole-body RF coil 41 arranged to surround the imaging space and a local RF coil 42 arranged close to the subject. The functions of the RF coil 40 are roughly divided into the transmission of high-frequency magnetic fields and the reception of NMR signals. Either the whole-body RF coil 41 or the local RF coil 42 may have both the transmission and reception functions, or both the whole-body RF coil 41 and the local RF coil 42 may be used for transmission and reception. In addition, multiple local RF coils 42 may be used simultaneously. The local RF coil 42 may also be set to be different according to the part of the subject.

[0037] The transmission circuit 50 outputs a high-frequency pulse signal corresponding to the Larmor frequency inherent to the target atomic nuclei placed in the static magnetic field to the RF coil 40 .

[0038] The receiving circuit 60 generates magnetic resonance (MR) data based on the NMR signal received by the RF coil 40 , and outputs the generated MR data to the processing circuit 100 .

[0039] The bed 70 includes a top plate 71 on which a subject is placed, and the top plate 71 can be moved in the vertical direction and the horizontal direction.

[0040] The input interface 80 receives input operations of various instructions and various information from the operator. Specifically, the input interface 80 is connected to the processing circuit 100, converts the input operation received from the operator into an electrical signal, and outputs it to the processing circuit 100. For example, the input interface 80 is implemented by a trackball, a switch button, a mouse, a keyboard, a touchpad that performs input operations by touching the operation surface, a touch screen that integrates a display screen and a touchpad, a non-contact input circuit using an optical sensor, and a sound input circuit. In addition, in this specification, the input interface 80 is not limited to components including physical operating components such as a mouse and a keyboard. For example, a processing circuit that receives an electrical signal corresponding to an input operation from an external input device that is separate from the device and outputs the electrical signal to a control circuit is also included in the example of the input interface 80.

[0041] The display 81 displays various information and images. Specifically, the display 81 is connected to the processing circuit 100 and converts the various information and image data sent from the processing circuit 100 into electrical signals for display and outputs them. For example, the display 81 is implemented as a liquid crystal monitor, an LED monitor, a touch panel, or the like.

[0042] Storage circuit 90 stores various data and programs. Specifically, storage circuit 90 is connected to processing circuit 100 and stores various data and programs input and output by each processing circuit. For example, storage circuit 90 can be implemented using semiconductor storage elements such as RAM (Random Access Memory) and flash memory, or a hard disk or optical disk.

[0043] The processing circuit 100 includes a bed control unit 101. The bed control unit 101 controls the operation of the bed 70 by outputting control electrical signals to the bed 70. For example, the bed control unit 101 receives an instruction from the operator via the input interface 80 to move the top 71. In accordance with the instruction, the bed control unit 101 activates a mechanism for moving the top 71 of the bed 70 to move the top 71. For example, when imaging a subject, the bed control unit 101 moves the top 71, on which the subject is placed, toward the imaging space.

[0044] The processing circuit 100 includes an acquisition unit 102. The acquisition unit 102 acquires MR data from the subject by executing various pulse sequences. Specifically, the acquisition unit 102 drives the gradient power supply 30, the transmission circuit 50, and the reception circuit 60 according to sequence execution data output from the processing circuit 100, thereby executing various pulse sequences. Sequence execution data is data indicating the pulse sequence and specifies information such as the timing and intensity of the current supplied by the gradient power supply 30 to the gradient coil 20, the timing and intensity of the high-frequency pulse signals supplied by the transmission circuit 50 to the RF coil 40, and the timing of magnetic resonance signal sampling by the reception circuit 60. The sequence execution data is pre-stored in the storage circuit 90 or generated by operator input in the input interface 80. The operator can also edit the sequence execution data pre-stored in the storage circuit 90. Furthermore, the acquisition unit 102 receives MR data output from the reception circuit 60 as a result of executing the pulse sequence and stores it in the storage circuit 90. At this time, the MR data stored in the storage circuit 90 is stored as k-space data. For example, when performing two-dimensional imaging, a phase encoding gradient magnetic field is applied to the surface of the slice selected by the slice selection gradient magnetic field. The k-space data according to the phase encoding amount of the applied gradient magnetic field is read out using a readout gradient magnetic field. The readout gradient magnetic field is also called a frequency encoding gradient magnetic field. For example, when performing three-dimensional imaging, a slice encoding gradient magnetic field and a phase encoding gradient magnetic field are applied, and the k-space data according to the encoding amount of the applied gradient magnetic field is read out using a readout gradient magnetic field. The slice selection gradient magnetic field, phase encoding gradient magnetic field, readout gradient magnetic field, and slice encoding gradient magnetic field described above are formed by the gradient magnetic fields generated by one or more of the X coils, Y coils, and Z coils described above.

[0045] The processing circuit 100 includes a corrector 103. The corrector 103 uses at least a portion of the k-space data acquired by the acquisition unit 102 to perform correction for suppressing motion artifacts caused by movement of the subject.

[0046] The processing circuit 100 includes an MR image generator 104. The MR image generator 104 generates various MR images using the k-space data acquired by the acquisition unit 102. For example, the MR image is generated by performing reconstruction processing such as Fourier transform on the k-space data. Furthermore, the MR image generator 104 can also perform image processing as post-processing on the reconstructed image.

[0047] The processing circuit 100 includes a display control unit 105. The display control unit 105 outputs the image generated by the MR image generating unit 104 to the display 81. Furthermore, the display 81 can also acquire an image stored in the storage circuit 90 or an external memory and display it.

[0048] The processing circuits 100 described above are each implemented by a processor. In this case, the processing functions of each processing circuit are stored in the storage circuit 90 in the form of a program that can be executed by a computer. Then, each processing circuit reads each program from the storage circuit 90 and executes it to implement the processing function corresponding to each program. In other words, each processing circuit that reads the status of each program has Figure 1 The functions of each part shown in each processing circuit.

[0049] Moreover, here, it is explained that each processing circuit is implemented by a single processor, but the implementation is not limited to this. A plurality of independent processors can also be combined to form each processing circuit, and each processor executes a program to implement each processing function. Moreover, the processing functions of each processing circuit can also be appropriately dispersed or concentrated in a single or multiple processing circuits. Figure 1 In the example shown, a single storage circuit 90 stores programs corresponding to respective processing functions. However, a plurality of storage circuits may be dispersedly arranged, and the processing circuits may read corresponding programs from the independent storage circuits.

[0050] The magnetic resonance imaging apparatus 1 further includes an image processing apparatus 200 . Figure 2 It is a structural block diagram of the image processing device 200 of the present invention.

[0051] The image processing device 200 is used to image an examination region of a subject during bipolar multi-echo acquisition, and includes an imaging k-space data acquisition unit 201, a template k-space data acquisition unit 202, a target k-space data generation unit 203, a kernel calculation unit 204, a synthesized k-space data generation unit 205, and an image generation unit 206. In the magnetic resonance imaging apparatus 1, the image processing device 200 may be configured independently or integrated into the processing circuit 100. The bipolar multi-echo acquisition method will be described in detail below.

[0052] like Figure 3 As shown, the imaging k-space data acquisition unit 201 acquires a plurality of imaging k-space data S1 to S3 by performing a first bipolar multi-echo acquisition D1 on an examination site of a subject.

[0053] The template k-space data acquisition unit 202 performs a second bipolar multi-echo acquisition D2 on the examination part of the subject, and acquires template k-space data S1' to S3' at echo times TE1' to TE3' corresponding to the echo times TE1 to TE3 of each of the plurality of imaging k-space data S1 to S3 acquired by the imaging k-space data acquisition unit 201, using a readout gradient polarity opposite to that of the first bipolar multi-echo acquisition D1.

[0054] In the first bipolar multi-echo acquisition D1, the acquired line data is converted into imaging k-space data S1 to S3. In the imaging k-space data S1 to S3, the areas at the edges (upper and lower edges) of the k-space data are referred to as the peripheral regions P, and the area at the center of the k-space data is referred to as the central region C (central portion). The imaging k-space data S1 to S3 are obtained by fully sampling the central region C (central portion) of k-space and undersampling the peripheral region P (edge ​​portion) of k-space.

[0055] Specifically, in the first shot, rightward line data L1 is output and acquired by an acquisition unit (not shown) at echo time TE1, leftward line data L2 is output and acquired by the acquisition unit at echo time TE2, and rightward line data L3 is output and acquired by the acquisition unit at echo time TE3, so that line data L1 to L3 are located at the uppermost portion of the peripheral region P of each k-space. In the second shot, rightward line data L7 is output and acquired by the acquisition unit at echo time TE1, leftward line data L8 is output and acquired by the acquisition unit at echo time TE2, and rightward line data L9 is output and acquired by the acquisition unit at echo time TE3, so that line data L7 to L9 are located at the uppermost portion of the central region C of each k-space.

[0056] like Figure 3 As shown in FIG, in each k-space, undersampled portions L4 to L6 are shown with dotted lines between line data L1 to L3 and line data L7 to L9. The undersampled portions L4 to L6 are where the data should be collected when the k-space is fully sampled. However, in order to shorten the imaging time, the data that should be located at the undersampled portions L4 to L6 is not output. In other words, there is no data at the undersampled portions L4 to L6 in the k-space. Figure 3 In the figure, line data L1 and the undersampled part L4 constitute the undersampled data S12 in the imaging k-space data S1, line data L2 and the undersampled part L5 constitute the undersampled data S22 in the imaging k-space data S2, and line data L3 and the undersampled part L6 constitute the undersampled data S32 in the imaging k-space data S3.

[0057] In the subsequent excitation, the central region C of each k-space is fully sampled to form fully sampled data, namely, imaging k-space data S11, imaging k-space data S21 and imaging k-space data S31. Figure 3 The lower peripheral area P is undersampled to form undersampled data, namely, undersampled data S13, undersampled data S23 and undersampled data S33.

[0058] In this way, multiple line data are acquired in the above acquisition method during multiple excitations. Line data L1, L7, etc. acquired at echo time TE1 constitute imaging k-space data S1, line data L2, L8, etc. acquired at echo time TE2 constitute imaging k-space data S2, and line data L3, L9, etc. acquired at echo time TE3 constitute imaging k-space data S3. Each imaging k-space data S1 to S3 has Figure 3 The imaging k-space data S1 to S3 are composed of the undersampled data in the peripheral region P and the fully sampled data in the central region C.

[0059] In the second bipolar multi-echo acquisition D2, if Figure 3 As shown, template k-space data S1'-S3' are acquired using a readout gradient polarity opposite to that of the first bipolar multi-echo acquisition D1. Furthermore, the acquisition unit acquires only the k-space data located in the central region (central portion) of k-space. Template k-space data S1'-S3' are data obtained by fully sampling the central region (central portion) of k-space.

[0060] Specifically, in the second bipolar multi-echo acquisition D2, in the first shot at the start of data acquisition, left-facing line data L1' is acquired at echo time TE1', right-facing line data L2' is acquired at echo time TE2', and left-facing line data L3' is acquired at echo time TE3'. In the second shot, left-facing line data L4' is acquired at echo time TE1', right-facing line data L5' is acquired at echo time TE2', and left-facing line data L6' is acquired at echo time TE3'. In this way, multiple lines of data are acquired using the above acquisition method over multiple shots. Line data L1', L4', etc. acquired at echo time TE1' constitute template k-space data S1', line data L2', L5', etc. acquired at echo time TE2' constitute template k-space data S2', and line data L3', L6', etc. acquired at echo time TE3' constitute template k-space data S3'.

[0061] The readout directions of the template k-space data S1 ′ to S3 ′ acquired at the echo times TE1 ′ to TE3 ′ are opposite to the readout directions of the imaging k-space data S1 to S3 acquired at the corresponding echo times TE1 to TE3 , respectively.

[0062] Regarding the order of the first bipolar multi-echo acquisition D1 and the second bipolar multi-echo acquisition D2, the second bipolar multi-echo acquisition D2 can be performed after the first bipolar multi-echo acquisition D1 is completed. Alternatively, after the first excitation of the first bipolar multi-echo acquisition D1 is completed, the first excitation of the second bipolar multi-echo acquisition D2 is performed, followed by the second excitation of the first bipolar multi-echo acquisition D1, and then the second excitation of the second bipolar multi-echo acquisition D2 is performed, and so on. The first bipolar multi-echo acquisition D1 and the second bipolar multi-echo acquisition D2 can be performed in various orders and are not limited. Furthermore, it is preferred that the first bipolar multi-echo acquisition D1 and the corresponding second bipolar multi-echo acquisition D2 be performed during a single breath-holding of the subject.

[0063] Moreover, in Figure 3 In the first bipolar multi-echo acquisition D1 and the second bipolar multi-echo acquisition D2 , an example is shown in which line data are acquired at three echo times to form three pieces of k-space data, respectively. However, the echo time is not limited to three and may be a plurality of times other than three.

[0064] The target k-space data generating unit 203 generates target k-space data without phase error of the imaging k-space data based on the template k-space data and the imaging k-space data acquired at the same echo time. The same echo time here refers to the echo time of acquiring the imaging k-space data and the echo time of acquiring the template k-space data corresponding to the imaging k-space data. Figure 3 The middle refers to the echo time TE1, TE1', the echo time TE2, TE2', or the echo time TE3, TE3'.

[0065] like Figure 4 As shown, the k-space data in the lower left corner is Figure 3 The template k-space data S2' acquired at echo time TE2' in the second bipolar multi-echo acquisition D2 has imaging k-space data S21 in the upper left corner, which is k-space data of the central portion of imaging k-space data S2 acquired at the same echo time TE2 (i.e., the echo time corresponding to echo time TE2' at which template k-space data S2' was acquired). The target k-space data generator 203 combines (adds, in this case, the template k-space data S2') with the imaging k-space data S21 to generate target k-space data T2 free of phase error.

[0066] Here, the target k-space data T2 is generated for the imaging k-space data S2 as an example. However, the target k-space data T2 is generated not only for the imaging k-space data S2, but also for each of the imaging k-space data S1, S3 and other imaging k-space data. Figure 3 、 Figure 4 For example, the target k-space data generator 203 combines (adds, in this case, the template k-space data S1') with the imaging k-space data S11 to generate target k-space data T1 free of phase error. It also combines (adds, in this case, the template k-space data S3') with the imaging k-space data S31 to generate target k-space data T3 free of phase error. Furthermore, it generates target k-space data T2 as described above. The target k-space data T1 to T3 are collectively referred to as target k-space data T.

[0067] The kernel calculation unit 204 calculates a plurality of kernels for correcting a phase error of at least one imaging k-space data including the imaging k-space data or generating unsampled data in the at least one imaging k-space data based on the target k-space data of the imaging k-space data and the imaging k-space data.

[0068] like Figure 5 As shown, three kernels are generated for each imaging k-space data S, and the three kernels are the first kernel k1 for correcting the phase of the k-space data in the peripheral area of ​​the imaging k-space data S, the second kernel k2 for correcting the phase of the k-space data in the central area of ​​the imaging k-space data S, and the third kernel k3 for generating unsampled data in the peripheral area of ​​the imaging k-space data S.

[0069] like Figure 5 As shown in (a), the kernel calculation unit 204 calculates the first kernel k1 based on the target k-space data T of the imaging k-space data S and the imaging k-space data S. Specifically, the kernel calculation unit 204 calculates the first kernel k1 based on the target k-space data T, especially the point t located in the center thereof, and the three points located on the line data L10, the three points located on the line data L20, and the three points located on the line data L30 in the imaging k-space data S. There is one row between the line data L10 to the line data L30, that is, there is one row between the line data L10 and the line data L20, and there is one row between the line data L20 and the line data L30. The first kernel k1 is obtained by Figure 5 The equation shown in (d), that is, the matrix multiplication (S*k=T), is calculated. Specifically, when the imaging k-space data S and the target k-space data T are known, the coefficient matrix k can be obtained as the first kernel k1.

[0070] exist Figure 5 In (a), line data L10 to line data L30 are separated by one line respectively, but they can also be separated by more than one identical line, such as two or three lines, and the number of separated lines can also be the same as the number of unsampled data lines between the sampled data. In short, the number of separated lines is not particularly limited. Figure 5In (a), three points on each line data are used as an example, but any other number of points may be used and is not particularly limited. In other words, as long as the first kernel k1 for correcting the phase of the k-space data in the peripheral region of the imaging k-space data S can be calculated, it will suffice.

[0071] like Figure 5 As shown in (b), the kernel calculation unit 204 calculates the second kernel k2 based on the target k-space data T of the imaging k-space data S and the imaging k-space data S. Specifically, the kernel calculation unit 204 calculates the second kernel k2 based on the target k-space data T, especially the point t located in the center thereof, and the three points located on the five adjacent line data L in the imaging k-space data S. The second kernel k2 is calculated by Figure 5 The equation shown in (d), that is, the matrix multiplication (S*k=T), is calculated. Specifically, when the imaging k-space data S and the target k-space data T are known, the coefficient matrix k can be obtained as the second kernel k2.

[0072] exist Figure 5 In (b), the example of three points located on each of five adjacent lines of line data L is used for explanation. However, the example may also include three or more adjacent odd-numbered lines of line data L, or may include a number of points other than three points, without particular limitation. In other words, as long as the second kernel k2 for phase correction of the k-space data in the central region of the imaging k-space data S can be calculated, any kernel k2 will suffice.

[0073] like Figure 5 As shown in (c), the kernel calculation unit 204 calculates the third kernel k3 based on the target k-space data T of the imaging k-space data S and the imaging k-space data S. Specifically, the kernel calculation unit 204 calculates the third kernel k3 based on the target k-space data T, especially the point t located in the center thereof, and the three points located on the line data L40 and the three points located on the line data L50 in the imaging k-space data S. The line data L40 and the line data L50 are separated by one line. The third kernel k3 is calculated by Figure 5 The equation shown in (d), that is, the matrix multiplication (S*k=T), is calculated. Specifically, when the imaging k-space data S and the target k-space data T are known, the coefficient matrix k can be obtained as the third kernel k3.

[0074] exist Figure 5 In (c), line data L40 and line data L50 are separated by one line, but they can also be separated by an odd number of lines, such as three or five lines, or more. Moreover, the number of separated lines can also be the same as the number of unsampled data lines between the sampled data. In short, the number of separated lines is not particularly limited. Figure 5In (c), three points on each line data are used as an example, but other numbers of points may be used and are not particularly limited. In other words, as long as the third kernel k3 of the unsampled data in the peripheral region that generates the imaging k-space data S can be calculated, it will suffice.

[0075] The synthesized k-space data generating unit 205 synthesizes the plurality of kernels with each of at least one imaging k-space data to generate synthesized k-space data.

[0076] like Figure 5 as well as Figure 6 As shown, three kernels generated for the imaging k-space data S, namely, a first kernel k1 , a second kernel k2 , and a third kernel k3 , are synthesized with the imaging k-space data S to generate synthesized k-space data HS.

[0077] Specifically, such as Figure 6 As shown, the phase of the point t100 of the line data L100 in the peripheral region P of the imaging k-space data S is corrected using the first kernel k1. Figure 6 The example in which the first kernel k1 is used to correct the points of the line data L100 in the peripheral region P of the imaging k-space data S is shown. However, in practice, all acquired line data in the peripheral region P of the imaging k-space data S can be corrected using the first kernel k1.

[0078] The second kernel k2 is used to correct the phase of point t200 of line data L200 in the central region C of the imaging k-space data S. Figure 6 In the example, correction of the line data L200 in the central region C of the imaging k-space data S using the second kernel k2 is shown. However, in practice, all line data in the central region C of the imaging k-space data S can be corrected using the second kernel k2.

[0079] The third kernel k3 is used to generate a point t300 of the undersampled portion L300 in the peripheral region P of the imaging k-space data S. Figure 6 The example in which the third kernel k3 is used to generate the points of the undersampled portion L300 in the peripheral region P of the imaging k-space data S is shown. However, in reality, the third kernel k3 can be used to generate line data of all undersampled portions in the peripheral region P of the imaging k-space data S.

[0080] In this way, after correcting the acquired line data of the imaging k-space data S using the first kernel k1 , the second kernel k2 , and the third kernel k3 and generating line data of the undersampled portion of the imaging k-space data S, synthesized k-space data HS is generated for the imaging k-space data S.

[0081] The image generator 206 generates an image of the examination site using the synthesized k-space data HS. Specifically, the image generator 206 performs Fourier transform and other processing on the synthesized k-space data HS to generate an MR image of the examination site.

[0082] In the above-described embodiment, the kernel calculation unit 204 calculates three kernels of each imaging k-space data, namely, the first kernel, the second kernel, and the third kernel.

[0083] It can also be configured so that the kernel calculation unit 204 calculates three kernels for correcting the phase error of the imaging k-space data having the same readout direction as the imaging k-space data or generating unsampled data in the imaging k-space data based on the target k-space data of the imaging k-space data and the imaging k-space data.

[0084] Alternatively, the kernels corresponding to a plurality of imaging k-space data having the same readout direction may be averaged or weighted averaged to generate an average kernel for the plurality of imaging k-space data, and the average kernel may be synthesized with each imaging k-space data to generate synthesized k-space data for each imaging k-space data.

[0085] Specifically, Figure 7 Take this as an example to illustrate. Figure 7 , three imaging k-space data S1 , S3 , and S5 having the same readout direction are shown, and for simplicity of the drawing, only one line of data of each of the imaging k-space data S1 , S3 , and S5 is shown.

[0086] The kernel calculation unit 204 calculates the first kernel, the second kernel, and the third kernel for the three imaging k-space data S1, S3, and S5, respectively. Figure 7 In the description, the first kernel is used as an example. The kernel calculation unit 204 averages or weighted averages the first kernel k11 calculated for the imaging k-space data S1, the first kernel k13 calculated for the imaging k-space data S3, and the first kernel k15 calculated for the imaging k-space data S5 to generate a first average kernel k10. Although not shown, the three calculated second kernels are averaged or weighted averaged to generate a second average kernel, and the three calculated third kernels are averaged or weighted averaged to generate a third average kernel.

[0087] The synthesized k-space data generator 205 synthesizes the first averaging kernel k10 , the second averaging kernel k10 , and the third averaging kernel k10 with the imaging k-space data S1 , S3 , and S5 to generate synthesized k-space data.

[0088] When the kernel calculation unit 204 calculates the kernel for each imaging k-space data set, the kernel for each individual imaging k-space data set may be inaccurate due to the influence of signal noise. As described above, by averaging or weighted averaging the kernels corresponding to a plurality of isotropic imaging k-space data sets, the accuracy of the kernel can be improved, thereby generating more accurate synthetic k-space data for each imaging k-space data set.

[0089] Below, based on Figure 8 A method of imaging an examination site of a subject will be described.

[0090] In step S11 , the imaging k-space data acquisition unit 201 acquires a plurality of imaging k-space data by performing first bipolar multi-echo acquisition on the examination site of the subject. The plurality of imaging k-space data are arranged such that adjacent imaging k-space data are read out in opposite directions.

[0091] In step S12, the template k-space data acquisition unit 202 performs a second bipolar multi-echo acquisition on the examination part of the subject, and acquires template k-space data with an opposite readout gradient polarity at an echo time corresponding to each echo time for acquiring multiple imaging k-space data. As a result, template k-space data with a readout direction opposite to that of each imaging k-space data is acquired, and the template k-space data is located in the central part of the k-space.

[0092] In step S13, the target k-space data generator 203 generates target k-space data free of phase error for the imaging k-space data based on the template k-space data and the imaging k-space data acquired at the same echo time. Specifically, the target k-space data generator 203 combines the template k-space data with the k-space data located in the center of the imaging k-space data acquired at the same echo time to generate target k-space data free of phase error.

[0093] In step S14, the kernel calculation unit 204 calculates a plurality of kernels for correcting the phase error of at least one imaging k-space data including the imaging k-space data or generating unsampled data in the at least one imaging k-space data based on the target k-space data of the imaging k-space data and the imaging k-space data. The plurality of kernels is a coefficient matrix including a first kernel for correcting the phase of the k-space data in the peripheral region of the imaging k-space data, a second kernel for correcting the phase of the k-space data in the central region of the imaging k-space data, and a third kernel for generating unsampled data in the peripheral region of the imaging k-space data.

[0094] In step S15, the synthesized k-space data generator 205 synthesizes the plurality of kernels with each of the at least one imaging k-space data to generate synthesized k-space data. Specifically, for each imaging k-space data, the kernel is synthesized with the imaging k-space data to generate phase-corrected, unsampled synthesized k-space data.

[0095] In step S16 , the image generator 206 generates an image of the examination region using the synthesized k-space data for each piece of imaging k-space data.

[0096] Furthermore, in step S14, the kernel calculation unit 204 may average or weighted average the first kernels of a plurality of isodirectional imaging k-space data having the same readout direction to generate a first average kernel, average or weighted average the second kernels of a plurality of isodirectional imaging k-space data to generate a second average kernel, and average or weighted average the third kernels of a plurality of isodirectional imaging k-space data to generate a third average kernel. Furthermore, in step S15, the synthesized k-space data generator 205 may synthesize the first, second, and third average kernels with each isodirectional imaging k-space data to generate synthesized k-space data.

[0097] In the above-described embodiment, the three generated kernels are capable of reconstructing (generating) unsampled imaging k-space data while performing phase correction on the imaging k-space data. Therefore, compared with the imaging method of the prior art in which the processing of decoding the phase error map and the phase correction processing are performed separately, more reliable and efficient imaging can be performed.

[0098] Moreover, in the above-mentioned embodiment, during the process of the subject holding his breath once, the first bipolar multi-echo acquisition and the corresponding second bipolar multi-echo acquisition can be performed to obtain imaging k-space data and the corresponding template k-space data. Therefore, the image reconstruction will not be affected by respiratory movement and errors will not be introduced. Compared with SENSE mapping scanning, more reliable imaging can be performed.

[0099] In the above embodiment, since more accurate and reliable phase correction and imaging can be performed, the accuracy of fat quantification can be improved in fat quantification processing such as water-fat segmentation.

[0100] As described above, although the above embodiments of the present invention have been described, these embodiments are shown as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other ways, and various omissions, substitutions, and modifications can be made without departing from the scope of the invention. These embodiments and their variations are included in the scope and spirit of the invention and are included in the invention described in the technical solution and its equivalents.

Claims

1. An image processing device for imaging an examination part of a subject in bipolar multi-echo acquisition, characterized in that: have: an imaging k-space data acquisition unit, which acquires a plurality of imaging k-space data by performing a first bipolar multi-echo acquisition on the examination part; a template k-space data acquisition unit that performs a second bipolar multi-echo acquisition on the examination site, acquiring a plurality of template k-space data at an echo time corresponding to an echo time for acquiring each of the plurality of imaging k-space data using a readout gradient polarity opposite to that of the first bipolar multi-echo acquisition; a target k-space data generating unit for generating target k-space data without phase error of the imaging k-space data based on the template k-space data and the imaging k-space data acquired at the same echo time; a kernel calculation unit for calculating, based on the target k-space data of the imaging k-space data and the imaging k-space data, a plurality of kernels for correcting a phase error of imaging k-space data having the same readout direction as the imaging k-space data or generating unsampled data in the imaging k-space data in the same direction; a synthetic k-space data generating unit for synthesizing the plurality of kernels with the isotropic imaging k-space data to generate synthetic k-space data; as well as an image generating unit that generates an image of the examination site using the synthesized k-space data; The above multiple kernels are coefficient matrices, The above multiple kernels include: a first kernel for correcting the phase of k-space data in a peripheral region of the imaging k-space data; a second kernel for correcting the phase of k-space data in a central region of the imaging k-space data; and The third kernel is used to generate unsampled data in the peripheral region of the imaging k-space data.

2. The image processing device according to claim 1, wherein The imaging k-space data is obtained by fully sampling the central part of the k-space and under-sampling the edge of the k-space. The template k-space data is data obtained by fully sampling the central portion of the k-space.

3. The image processing device according to claim 2, wherein The target k-space data generating unit generates the target k-space data by combining the template k-space data and the k-space data in the central portion of the imaging k-space data acquired at the same echo time.

4. The image processing device according to claim 1, wherein The above-mentioned isotropic imaging k-space data is multiple, The kernel calculation unit calculates the first kernel, the second kernel, and the third kernel for each of the isotropic imaging k-space data, and averages or weighted averages the calculated plurality of first kernels to generate a first average kernel, averages or weighted averages the calculated plurality of second kernels to generate a second average kernel, and averages or weighted averages the calculated plurality of third kernels to generate a third average kernel. The synthetic k-space data generating unit generates synthetic k-space data by synthesizing the first averaging kernel, the second averaging kernel, and the third averaging kernel with each of the isotropic imaging k-space data.

5. An image processing method for imaging an examination part of a subject in bipolar multi-echo acquisition, characterized in that: have: an imaging k-space data acquisition step, acquiring a plurality of imaging k-space data by performing a first bipolar multi-echo acquisition on the examination site; a template k-space data acquisition step of performing a second bipolar multi-echo acquisition on the examination site, acquiring a plurality of template k-space data at an echo time corresponding to the echo time of each of the plurality of imaging k-space data, using a readout gradient polarity opposite to that of the first bipolar multi-echo acquisition; a target k-space data generating step of generating target k-space data without phase error of the imaging k-space data based on the template k-space data and the imaging k-space data acquired at the same echo time; a kernel calculation step of calculating, based on the target k-space data of the imaging k-space data and the imaging k-space data, a plurality of kernels for correcting a phase error of imaging k-space data in the same direction as the imaging k-space data having the same readout direction as the imaging k-space data or generating unsampled data in the imaging k-space data in the same direction; a synthetic k-space data generating step of synthesizing the plurality of kernels and the isotropic imaging k-space data to generate synthetic k-space data; and an image generating step of generating an image of the examination site using the synthesized k-space data; The above multiple kernels are coefficient matrices, The above multiple kernels include: a first kernel for correcting the phase of k-space data in a peripheral region of the imaging k-space data; a second kernel for correcting the phase of k-space data in a central region of the imaging k-space data; and The third kernel is used to generate unsampled data in the peripheral region of the imaging k-space data.

6. The image processing method according to claim 5, wherein: The imaging k-space data is obtained by fully sampling the central part of the k-space and under-sampling the edge of the k-space. The template k-space data is data obtained by fully sampling the central portion of the k-space.

7. The image processing method according to claim 6, wherein: In the target k-space data generating step, the target k-space data is generated by combining the template k-space data and the k-space data at the center of the imaging k-space data acquired at the same echo time.

8. The image processing method according to claim 5, wherein: The above-mentioned isotropic imaging k-space data is multiple, In the kernel calculation step, the first kernel, the second kernel, and the third kernel are calculated for each of the isotropic imaging k-space data, and the plurality of first kernels calculated are averaged or weighted averaged to generate a first average kernel, the plurality of second kernels calculated are averaged or weighted averaged to generate a second average kernel, and the plurality of third kernels calculated are averaged or weighted averaged to generate a third average kernel. In the synthetic k-space data generating step, the first averaging kernel, the second averaging kernel, and the third averaging kernel are synthesized with each of the isotropic imaging k-space data to generate synthetic k-space data.

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