System and method for magnetic resonance imaging

Abstract

The present specification provides a system for MRI. The system includes an acquisition module and a quantitative measurement module. The acquisition module can be used to acquire at least two sets of k-space data corresponding to at least two frames. Each set of the at least two sets of k-space data is acquired from at least two layer positions of a subject simultaneously using a magnetic resonance imaging scanner in one of the at least two frames, with a wait time after a preparation pulse is applied in the frame. The quantitative measurement module can be used to generate at least two quantitative maps of the at least two layer positions based on the at least two sets of k-space data. In the at least two frames, a phase modulation is applied to at least one target layer position of the at least two layer positions for inter-layer separation.

Description

[0001] Priority Statement

[0002] This specification claims priority to U.S. Application No. 17 / 305,055, filed June 30, 2021, which is a partial continuation of U.S. Application No. 16 / 823,274, filed March 18, 2020, or U.S. Application No. 16 / 658,297, filed October 21, 2019. The contents of all three U.S. applications are incorporated herein by reference. Technical Field

[0003] This specification generally relates to magnetic resonance imaging (MRI), and more specifically, to systems and methods for simultaneously making quantitative measurements of multiple slice locations of an object. Background Technology

[0004] MRI is an important clinical tool for diagnosing and / or treating diseases. In some cases, one or more quantitative parameters, such as longitudinal relaxation time (T1), transverse relaxation time (T2), and transverse relaxation decay (T2*), can be determined by performing MRI scans on a subject. These quantitative parameters reflect the subject's physiological characteristics and can be used for disease diagnosis. Traditionally, quantitative measurements are performed separately at different slice locations, which is inefficient. Simultaneous multi-slice (SMS) imaging (or multi-band imaging) is a promising technique for accelerating MR scans, allowing simultaneous excitation of multiple slice locations. Therefore, it is desirable to provide systems and methods for quantitative measurements of subjects with improved efficiency by incorporating SMS imaging techniques. Summary of the Invention

[0005] According to another aspect of this specification, an MRI system is provided. The system may include an acquisition module and a quantitative measurement module. The acquisition module is configured to acquire at least two sets of k-space data corresponding to at least two frames, wherein in one of the at least two frames, an MRI scanner is used to simultaneously acquire each set of k-space data from at least two slice locations of a subject, with a waiting time following the application of a preparation pulse in the frame. The quantitative measurement module is configured to generate at least two quantitative maps of the at least two slice locations based on the at least two sets of k-space data. In the at least two frames, phase modulation is applied to at least one target slice location among the at least two slice locations for slice separation.

[0006] In some embodiments, for each target layer in the at least one target layer location, the phase of the target layer location is modulated along the spatial dimension according to the phase modulation mechanism of the frame during each frame in at least two frames.

[0007] In some embodiments, for each of the at least one target layer locations, the phase of the target layer location is modulated along the time dimension such that the phase modulation mechanism of a pair of adjacent frames of the at least two frames is different.

[0008] In some embodiments, at least two target layer images at the layer location and at least two quantitative images at at least two layer locations. Figure 1 It is generated.

[0009] In some embodiments, to generate at least two quantitative maps for at least two layer locations based on at least two sets of k-space data, at least one processor may be configured to instruct the system to determine one or more reconstruction parameters based on the at least two sets of k-space data, and to construct an optimization function, the optimization function including the quantitative maps for the at least two layer locations, at least two target layer images for the at least two layer locations, the one or more reconstruction parameters, and the at least two sets of k-space data. For each of the plurality of layer locations, the at least one processor may be configured to generate the at least two quantitative maps and the at least two target layer images for the at least two layer locations by solving the optimization function.

[0010] In some embodiments, the optimization function is constructed based on a signal model that establishes the relationship between the waiting time and quantitative parameters of the quantitative plot corresponding to the at least two layer locations.

[0011] In some embodiments, in order to determine one or more reconstruction parameters based on at least two sets of k-space data, for each of the at least two layer locations, at least one processor may be configured to instruct the system to generate a reference layer image of the layer location based on the at least two sets of k-space data, and to include at least two coil sensitivity maps corresponding to each of the at least two layer locations as part of the one or more reconstruction parameters based on the reference layer image of the at least two layer locations.

[0012] In some embodiments, for each of the at least two frames, the corresponding set of k-space data is a set of undersampled k-space data collected according to the intra-frame undersampling mode.

[0013] In some embodiments, the undersampling patterns of a pair of adjacent frames in the at least two frames are interleaved.

[0014] In some embodiments, the preparation pulse includes an inverted pulse, and the quantitative map for each of the at least two layer locations includes a T1 map.

[0015] According to another aspect of this specification, a non-transitory computer-readable storage medium is provided, comprising a set of instructions for MRI. When executed by at least one processor of the system, the set of instructions causes the system to perform a method. The method may include acquiring at least two sets of k-space data corresponding to at least two frames, wherein, in one of the at least two frames, a magnetic resonance imaging scanner is used to simultaneously acquire each of the at least two sets of k-space data from at least two slice locations of an object, with a waiting time following the application of a preparation pulse in the frame. The method may further include generating at least two quantitative maps of the at least two slice locations based on the at least two sets of k-space data, wherein, in the at least two frames, phase modulation is applied to at least one target slice location of the at least two slice locations for interslice separation.

[0016] Some additional features of this specification may be described in the following description. These additional features will become apparent to those skilled in the art from the study of the following description and the accompanying drawings, or from an understanding of the production or operation of the embodiments. The features of this specification can be realized by practice or use of various aspects of the methods, tools, and combinations set forth in the detailed examples discussed below. Attached Figure Description

[0017] This specification will be further described through exemplary embodiments. These exemplary embodiments will be described in detail with reference to the accompanying drawings. These embodiments are non-limiting exemplary embodiments, in which the same numbers in the figures denote similar structures, wherein:

[0018] Figure 1 These are schematic diagrams of exemplary MRI systems according to some embodiments of this specification;

[0019] Figure 2 These are schematic diagrams of exemplary MRI scanners shown according to some embodiments of this specification;

[0020] Figure 3 These are schematic diagrams of exemplary hardware and / or software components of a computing device according to some embodiments of this specification;

[0021] Figure 4 These are schematic diagrams of exemplary hardware and / or software components of a mobile device according to some embodiments of this specification;

[0022] Figure 5 This is a block diagram of an exemplary processing apparatus according to some embodiments of this specification;

[0023] Figure 6 This is a flowchart illustrating an exemplary procedure for multi-slice simultaneous MRI according to some embodiments of this specification;

[0024] Figure 7 This is a schematic diagram illustrating an exemplary bSSFP pulse sequence according to some embodiments of this specification;

[0025] Figures 8A and 8B are exemplary aliased images of two layers in the heart, illustrating some embodiments according to this specification;

[0026] Figures 9A and 9B are exemplary reference layer images of two layer locations in the heart, as shown in some embodiments of this specification;

[0027] Figure 10 These are exemplary cardiac layer images shown according to some embodiments of this specification;

[0028] Figure 11 This is a schematic diagram of an exemplary bSSFP pulse sequence according to some embodiments of this specification;

[0029] Figure 12 This is a schematic diagram of an exemplary FSE pulse sequence according to some embodiments of this specification;

[0030] Figure 13 This is a schematic diagram of an exemplary EPI pulse sequence according to some embodiments of this specification;

[0031] Figure 14 This is a flowchart illustrating an exemplary procedure for multi-slice simultaneous MRI according to some embodiments of this specification;

[0032] Figure 15 This is a flowchart illustrating an exemplary process for reconstructing at least two reference layer images according to some embodiments of this specification;

[0033] Figure 16 This is a schematic diagram of exemplary phase modulation and undersampling modes in MR scanning according to some embodiments of this specification;

[0034] Figure 17 This is a schematic diagram illustrating an exemplary process for generating a reference layer image according to some embodiments of this specification;

[0035] Figure 18 These are exemplary phase modulation mechanisms for the first and second layer positions in a frame, as shown in some embodiments of this specification;

[0036] Figure 19 These are layer images corresponding to the same cardiac phase of a patient, as shown in some embodiments of this specification;

[0037] Figure 20 These are exemplary image sequences of two layer locations of a patient's heart as shown in some embodiments of this specification;

[0038] Figure 21 This is a flowchart illustrating an exemplary process for generating at least two quantitative maps at at least two layer locations, according to some embodiments of this specification;

[0039] Figure 22 This is a flowchart illustrating an exemplary process for at least two quantitative maps at at least two layer locations, according to some embodiments of this specification;

[0040] Figure 23 These are schematic diagrams illustrating exemplary pulse sequences according to some embodiments of this specification; and

[0041] Figure 24 This is a schematic diagram of an exemplary pulse sequence according to some embodiments of this specification. Detailed Implementation

[0042] This document provides systems and methods for non-invasive biomedical imaging, such as for disease diagnosis or research purposes. While the systems and methods disclosed herein are primarily described in relation to quantitative measurements and simultaneous multi-slice (SMS) imaging of subjects within magnetic resonance imaging (MRI) systems, it should be understood that this is for illustrative purposes only. The systems and methods described herein can be applied to any other imaging system. In some embodiments, the imaging system may include a single-modality imaging system and / or a multimodality imaging system. A single-modality imaging system may include, for example, an MRI system. A multimodality imaging system may include, for example, an X-ray imaging magnetic resonance imaging (X-ray-MRI) system, a single-photon emission computed tomography (SPECT-MRI) system, a digital subtraction angiography magnetic resonance imaging (DSA-MRI) system, a computed tomography magnetic resonance imaging (MRI-CT) system, a positron emission tomography (PET-MRI) system, and the like.

[0043] One aspect of this specification relates to a system and method for simultaneously imaging at least two (or more) slice locations of an object using an MRI scanner. The at least two (or more) slice locations may include a first slice location and at least one second slice location. Typically, additional reference scans may be required to obtain reference data for each slice location for inter-slice separation. For example, reference slice images of at least two (or more) slice locations can be reconstructed, and the coil sensitivity distribution of different receiving coils can be determined. Slice images of each individual slice location can be separated from the aliased images acquired in SMS imaging based on this coil sensitivity distribution. However, additional reference scans may result in additional scan time and diminish the advantages of SMS imaging.

[0044] To avoid requiring additional reference scans, the systems and methods of this specification can utilize automatically calibrated multi-band imaging techniques. For example, in each of at least two frames (or more frames), the systems and methods can enable an MRI scanner to apply at least two (or more) phase-encoding (PE) steps to each slice location to obtain a set of echo signals. In each of at least two frames (or more frames), in each of at least some of the at least two (or more) PE steps, a phase-modulated magnetic field gradient (also simply referred to as a phase-modulated gradient) can be applied such that for multiple PE steps applied in a pair of at least two frames (or more frames) corresponding to PE lines at the same location in k-space, multiple phase differences are different, each of these multiple phase differences being the difference between at least one second slice location and a first slice location at one of the at least two (or more) PE steps.

[0045] By applying a phase modulation gradient, the system and method can reconstruct one or more images based on a set of echo signals acquired in a frame without additional reference scans, where each layer image can represent a single layer location in a frame. For example, the system and method can reconstruct aliased images of at least two(more) layer locations in each frame based on the corresponding set of echo signals, and generate reference layer images of at least two(more) layer locations based on the aliased images (e.g., by performing a linear combination of the aliased images). The system and method can further reconstruct layer images based on the aliased images and the reference layer images. In this way, the system and method can eliminate the need for additional reference scans, reduce scan time, and / or improve imaging efficiency and / or patient experience.

[0046] Furthermore, in some embodiments, the phase modulation described herein can be achieved either alone or in combination with a phase-modulated radio frequency (RF) excitation pulse applied by the Z-coil of an MRI scanner. Conventional methods for phase modulation in an automated calibration SMS over at least two frames (or more), such as the Controlled Aliasing Parallel Accelerated Imaging (CAIPIRINHA) technique using only phase-modulated RF excitation pulses, can limit pulse sequences without echo sequences to acquiring only one PE line data per RF excitation pulse. The systems and methods provided in this specification are applicable not only to spoiled gradient echo (spGRE) sequences but also to balanced steady-state free precession (bSSFP) pulse sequences. The disclosed techniques can also be applied to sequences with echo sequences, such as echo planar imaging (EPI) pulse sequences and fast spin echo (FSE) pulse sequences.

[0047] In some embodiments, to further accelerate the MR scanning process, the systems and methods of this specification may utilize ATOMICS, which combines automatically calibrated multi-band imaging techniques with compressed sensing (CS) techniques. For example, the systems and methods may acquire at least two sets of undersampled k-space data corresponding to at least two frames (or more frames). Each of multiple sets of undersampled k-space data can be acquired simultaneously from multiple slice locations of an object in one of the at least two frames (or more frames) using an MRI scanner. Each set of undersampled k-space data can be acquired from at least two (or more) slice locations of an object in each of the at least two frames (or more frames) using an MRI scanner. The systems and methods may reconstruct at least two reference slice images based on the at least two frames (or more frames) of undersampled k-space data. Each of the at least two reference slice images may represent one slice location from at least two (or more) slice locations in more than one of the at least two frames (or more frames). The systems and methods may also reconstruct at least two (or more) image sequences based on the undersampled k-space data and the at least two reference slice images. Each of the at least two (or more) image sequences may correspond to one of the at least two (or more) layer positions, and includes at least two layer images of the corresponding layer position in at least two (or more) frames.

[0048] By using ATOMICS, single-band reference layer images can be generated based on undersampled k-space data, eliminating the need for additional reference scans. Furthermore, only a portion of the k-space data needs to be collected via CS technology, resulting in higher acceleration and improved imaging efficiency. For example, if two layer locations of a patient's heart are scanned simultaneously with an in-plane undersampling factor of 8 (e.g., 15 lines per frame), a 16-fold acceleration can be achieved. Whole-heart cine imaging can be completed in a short time (e.g., below a threshold time, such as 12 seconds), allowing the patient to breathe freely during the scan.

[0049] In some embodiments, the systems and methods of this specification can simultaneously generate quantitative maps of at least two(multiple) slice locations of an object by combining SMS imaging techniques and quantitative measurement techniques. For example, the systems and methods can acquire at least two sets of k-space data corresponding to at least two (multiple) frames. Each of the at least two sets of k-space data can be acquired simultaneously from at least two(multiple) slice locations of the object using an MRI scanner in one of the at least two (multiple) frames, with a waiting time following the application of a preparation pulse in that frame. The systems and methods can generate at least two quantitative maps of at least two(multiple) slice locations based on the at least two sets of k-space data. In some embodiments, the waiting times in the at least two (multiple) frames can be different. In the at least two (multiple) frames, phase modulation is applied to at least one target slice location in the at least two(multiple) slice locations for interslice separation. In some embodiments, at least two target slice images of at least two(multiple) slice locations can be combined with at least two quantitative images of at least two(multiple) slice locations. Figure 1 It is generated.

[0050] Traditionally, quantitative measurements are performed separately for different layer locations. For example, for each layer location, k-space data corresponding to different inversion times can be obtained through MRI scans of that layer, and the T1 map of the layer location can be determined based on the k-space data using a curve fitting algorithm. This process is time-consuming and provides an uncomfortable scanning experience for the subject. Compared to traditional quantitative measurement techniques, this system and method can simultaneously generate quantitative maps of multiple layer locations using SMS imaging technology, which is more efficient by, for example, reducing scan time.

[0051] Furthermore, this system and method can combine automatically calibrated multi-band imaging techniques and / or CS techniques, gaining the advantages of these techniques. CS techniques may require only partial k-space data collection (i.e., undersampled k-space data), thus improving imaging efficiency. Automatically calibrated multi-band imaging techniques can be implemented by applying phase modulation at one or more of at least two (or more) layer locations for interlayer separation, avoiding the additional scans required to generate reference layer images and preventing errors that may occur during additional scans.

[0052] Figure 1 This is a schematic diagram of an exemplary MRI system 100 according to some embodiments of this specification. Figure 1 As shown, the MRI system 100 may include an MRI scanner 110, a processing device 120, a storage device 130, one or more terminals 140, and a network 150. In some embodiments, the scanner 110, processing device 120, storage device 130, and terminal 140 may be connected to and / or communicate with each other via wireless connections, wired connections, or combinations thereof. The connections between the components in the MRI system 100 may be variable. For example, the MRI scanner 110 may be connected to the processing device 120 via the network 150. As another example, the MRI scanner 110 may be directly connected to the processing device 120.

[0053] MRI scanner 110 can be configured to scan an object (or a portion of an object) to acquire image data, such as echo signals (or MRI signals) associated with the object. For example, MRI scanner 110 can detect at least two(multiple) echo signals by applying a sequence of MR pulses to the object. In some embodiments, MRI scanner 110 may include, for example, a main magnet, gradient coils (or also referred to as spatial coding coils), radio frequency (RF) coils, etc. Figure 2 In some embodiments, depending on the type of main magnet, the MRI scanner 110 may be a permanent magnet MRI scanner, a superconducting magnet MRI scanner, or a resistive electromagnet MRI scanner, etc. In some embodiments, depending on the magnetic field strength, the MRI scanner 110 may be a high-field MRI scanner, a medium-field MRI scanner, or a low-field MRI scanner, etc.

[0054] The object scanned by the MRI scanner 110 can be biological or non-biological. For example, the object may include a patient, a man-made object, etc. As another example, the object may include a specific part, organ, tissue, and / or physical point of a patient. As mere examples, the object may include the head, brain, neck, body, shoulder, arm, chest, heart, stomach, blood vessels, soft tissue, knee joint, foot, etc., or combinations thereof.

[0055] For ease of explanation, Figure 1 It provides a coordinate system 160 including the X-axis, Y-axis and Z-axis. Figure 1 The X and Z axes shown can be horizontal, and the Y axis can be vertical. As shown in the figure, viewed from the front of the MRI scanner 110, the positive X direction along the X axis can be from the right side to the left side of the MRI scanner 110; along... Figure 1 The positive Y-axis shown can be from the bottom to the top of the MRI scanner 110; Figure 1The positive Z-direction along the Z-axis shown can refer to the direction in which the object moves out of the scanning channel (or aperture) of the MRI scanner 110. Further description of the MRI scanner 110 can be found elsewhere in this specification. For example, see... Figure 2 And its description.

[0056] In some embodiments, the MRI scanner 110 may be instructed to select an anatomical layer of the object along a slice selection direction and scan the anatomical layer to acquire at least two(more) echo signals from that layer. During scanning, spatial encoding within the layer can be implemented using spatial encoding coils (e.g., X-coil and Y-coil) along the phase encoding direction and frequency encoding direction. The echo signals can be sampled and the corresponding sampled data can be stored in a k-space matrix for image reconstruction. For illustrative purposes, the slice selection direction herein may correspond to the Z-direction defined by coordinate system 160 and the Kz-direction in k-space; the phase encoding direction may correspond to the Y-direction defined by coordinate system 160 and the Ky-direction in k-space; and the frequency encoding direction may correspond to the X-direction defined by coordinate system 160 and the Kx-direction in k-space. It should be noted that the slice selection direction, phase encoding direction, and frequency encoding direction may be modified as needed without departing from the scope of this specification. Further description of the MRI scanner 110 can be found elsewhere in this specification. For example, see Figure 2 And its explanation.

[0057] Processing device 120 can process data and / or information acquired from MRI scanner 110, storage device 130, and / or terminal 140. Processing device 120 can simultaneously generate at least two quantitative maps at at least two (or more) layer locations based on at least two sets of k-space data acquired in at least two (or more) layer locations within at least two (or more) frames. In some embodiments, processing device 120 can be a single server or a group of servers. The server group can be centralized or distributed. In some embodiments, processing device 120 can be local or remote. For example, processing device 120 can access information and / or data from MRI scanner 110, storage device 130, and / or terminal 140 via network 150. Alternatively, processing device 120 can be directly connected to MRI scanner 110, terminal 140, and / or storage device 130 to access information and / or data. In some embodiments, processing device 120 can be implemented on a cloud platform. For example, the cloud platform can include private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, inter-cloud cloud, multi-cloud, or combinations thereof. In some embodiments, the processing device 120 may be composed of a device having, for example, Figure 3 The computing device 300 with one or more of the aforementioned components is used to implement this.

[0058] Storage device 130 may store data, instructions, and / or any other information. In some embodiments, storage device 130 may store data acquired from MRI scanner 110, processing device 120, and / or terminal 140. In some embodiments, storage device 130 may store data and / or instructions that processing device 120 can execute, or that processing device 120 can use to execute, the exemplary methods described herein.

[0059] In some embodiments, storage device 130 may be connected to network 150 to communicate with one or more other components of MRI system 100 (e.g., MRI scanner 110, processing device 120, and / or terminal 140). One or more components of MRI system 100 may access data or instructions stored in storage device 130 via network 150. In some embodiments, storage device 130 may be part of processing device 120 or terminal 140.

[0060] Terminal 140 may be configured to enable user interaction between a user and MRI system 100. For example, terminal 140 may receive instructions from the user to have MRI scanner 110 scan an object. Alternatively, terminal 140 may receive processing results (e.g., slice images characterizing the slice location of an object) from processing device 120 and display the results to the user. In some embodiments, terminal 140 may be connected to and communicate with MRI scanner 110, processing device 120, and / or storage device 130. In some embodiments, terminal 140 may include mobile device 140-1, tablet computer 140-2, laptop computer 140-3, etc., or combinations thereof. In some embodiments, terminal 140 may include input devices, output devices, etc. Input devices may include alphanumeric keys and other keys that can be entered via a keyboard, a touchscreen (e.g., with haptic or haptic feedback), voice input, eye-tracking input, brain monitoring system input, or any other similar input mechanism. Input information received through the input device may be transmitted to processing device 120 via, for example, a bus for further processing. Other types of input devices may include cursor control devices, such as a mouse, trackball, or cursor arrow keys. Output devices may include a display, speakers, a printer, or a combination thereof. In some embodiments, terminal 140 may be part of processing device 120 or MRI scanner 110.

[0061] Network 150 may include any suitable network that facilitates the exchange of information and / or data between the MRI system 100 and the MRI system 100. In some embodiments, one or more components of the MRI system 100 (e.g., MRI scanner 110, processing device 120, storage device 130, terminal 140, etc.) may transmit information and / or data with one or more other components of the MRI system 100 via network 150. For example, processing device 120 may acquire image data (e.g., echo signals) from MRI scanner 110 via network 150. As another example, processing device 120 may acquire user instructions from terminal 140 via network 150.

[0062] This description is intended to be illustrative, not limiting. Many alternatives, modifications, and variations will be apparent to those skilled in the art. The features, structures, methods, and characteristics of the exemplary embodiments described herein can be combined in various ways to obtain additional and / or alternative exemplary embodiments. In some embodiments, the MRI system 100 may include one or more additional components and / or one or more components described above may be omitted. Alternatively or additionally, two or more components of the MRI system 100 may be integrated into a single component. For example, processing device 120 may be integrated into MRI scanner 110. As another example, a component of the MRI system 100 may be replaced by another component capable of performing the function of that component. In some embodiments, storage device 130 may be a data storage device including a cloud computing platform, such as a public cloud, private cloud, community cloud, and hybrid cloud. However, these variations and modifications do not depart from the scope of this specification.

[0063] Figure 2 This is a schematic diagram of an exemplary MRI scanner 110 according to some embodiments of this specification. One or more components of the MRI scanner 110 are... Figure 2 As shown, the main magnet 201 can generate a first magnetic field (or main magnetic field), which can be applied to an object (or test subject) exposed to the field. The main magnet 201 can include a resistive magnet or a superconducting magnet, both of which require a power source (not shown) to operate. Optionally, the main magnet 201 can include a permanent magnet. The main magnet 201 can include holes for placing the object inside. The main magnet 201 can also control the uniformity of the generated main magnetic field. Some shim coils can be included in the main magnet 201. The shim coils placed in the gaps of the main magnet 201 can compensate for non-uniformity of the magnetic field of the main magnet 201. The shim coils can be charged by a shim power source.

[0064] Gradient coil 202 can be located within main magnet 201. Gradient coil 202 can generate a second magnetic field (or gradient field, including gradient fields Gx, Gy, and Gz). The second magnetic field can be superimposed on the main field generated by main magnet 201 and distort the main field, so that the magnetic orientation of the protons of the object can vary according to their positions within the gradient field, thereby encoding spatial information into an MR signal generated from the region of the image object. Gradient coil 202 may include an X coil (e.g., for generating a gradient field Gx corresponding to the X direction), a Y coil (e.g., for generating a gradient field Gy corresponding to the Y direction), and / or a Z coil (e.g., for generating a gradient field Gz corresponding to the Z direction). Figure 2 (Not shown in the image). In some embodiments, the Z coil may be based on a Maxwell coil design, while the X and Y coils may be based on a Golay coil configuration. The three sets of coils can generate three different magnetic fields for position encoding. Gradient coil 202 can allow spatial encoding of the MR signal for image construction. Gradient coil 202 can be connected to one or more of X gradient amplifier 204, Y gradient amplifier 205, or Z gradient amplifier 206. One or more of the three amplifiers can be connected to waveform generator 216. Waveform generator 216 can generate gradient waveforms applied to X gradient amplifier 204, Y gradient amplifier 205, and / or Z gradient amplifier 206. The amplifiers can amplify the waveforms. The amplified waveforms can be applied to one of the coils in gradient coil 202 to generate magnetic fields along the X, Y, or Z axes, respectively. Gradient coil 202 can be designed for closed-aperture MRI scanners or open-aperture MRI scanners. In some cases, all three sets of coils in gradient coil 202 can be excited, thereby generating three gradient fields. In some embodiments of this specification, the X coil and Y coil can be excited to generate gradient fields in the X and Y directions, respectively. As used herein, Figure 2 The description of the X-axis, Y-axis, Z-axis, X direction, Y direction, and Z direction is consistent with... Figure 1 Those that are the same or similar as those described in the text.

[0065] In some embodiments, the radio frequency (RF) coil 203 may be located within the main magnet 201 and function as a transmitter, receiver, or both. The RF coil 203 may be connected to an RF electronics device 209, which may be configured or used as one or more integrated circuits (ICs) for use as waveform transmitters and / or waveform receivers. The RF electronics device 209 may be connected to an RF power amplifier (RFPA) 207 and an analog-to-digital converter (ADC) 208.

[0066] When used as a transmitter, RF coil 203 can generate an RF signal that provides a third magnetic field for generating an MR signal related to a region of the image. The third magnetic field can be perpendicular to the main magnetic field. Waveform generator 216 can generate RF pulses. These RF pulses can be amplified by RFPA 207, processed by RF electronics 209, and applied to RF coil 203 to generate an RF signal in response to a strong current generated by RF electronics 209 based on the amplified RF pulses.

[0067] When used as a receiver, the RF coil can be responsible for detecting the echo signal. After excitation, the echo signal generated by the object can be sensed by the RF coil 203. The receiver amplifier can then receive the sensed echo signal from the RF coil 203, amplify the sensed echo signal, and provide the amplified echo signal to the ADC 208. The ADC 208 can convert the echo signal from an analog signal to a digital signal. The digital echo signal can then be sent to the processing device 120 for sampling.

[0068] In some embodiments, gradient coil 202 and RF coil 203 may be circumferentially positioned relative to the object. Those skilled in the art will understand that the main magnet 201, gradient coil 202, and RF coil 203 may be arranged around the object in various configurations.

[0069] In some embodiments, RFPA 207 can amplify RF pulses (e.g., the power of the RF pulse, the voltage of the RF pulse) to generate amplified RF pulses to drive RF coil 203. RFPA 207 may include a transistor-based RFPA, a vacuum tube-based RFPA, or any combination thereof. A transistor-based RFPA may include one or more transistors. A vacuum tube-based RFPA may include transistors, tetrodes, klystrons, or any combination thereof. In some embodiments, RFPA 207 may include a linear RFPA or a non-linear RFPA. In some embodiments, RFPA 207 may include one or more RFPAs.

[0070] In some embodiments, the MRI scanner 110 may further include an object positioning system (not shown). The object positioning system may include an object holder and a transport device. The object may be placed on the object holder and positioned within a hole in the main magnet 201 by the transport device.

[0071] MRI systems (e.g., MRI system 100 disclosed herein) are generally used to acquire internal images of a patient for a specific region of interest (ROI), which can be used for purposes such as diagnosis, treatment, or a combination thereof. The MRI system includes a main magnet assembly (e.g., main magnet 201) for providing a strong, uniform main magnetic field to align the individual magnetic moments of hydrogen atoms within the patient's body. In this process, hydrogen atoms oscillate around their magnetic poles at their characteristic Larmor frequencies. If tissue corresponds to another magnetic field tuned to a Larmor frequency, the hydrogen atoms absorb additional energy, thereby rotating the net alignment torque of the hydrogen atoms. The additional magnetic field can be provided by an RF excitation signal (e.g., an RF signal generated by RF coil 203). When the additional magnetic field is removed, the magnetic moments of the hydrogen atoms rotate back to alignment with the main magnetic field, thereby emitting an echo signal. The echo signals are received and processed to form an MR image. T1 relaxation can be a process of net magnetization increasing / returning to an initial maximum value parallel to the main magnetic field. T1 can be the time constant for longitudinal magnetization regrowth (e.g., along the main magnetic field). T2 relaxation can be a process of attenuation or dephasing of the transverse component of magnetization. T2 can be the time constant for transverse magnetization decay / dephase.

[0072] If the main magnetic field is uniform across the entire patient's body, the RF excitation signal can non-selectively excite all hydrogen atoms in the sample. Therefore, to image a specific portion of the patient's body, magnetic field gradients Gx, Gy, and Gz in the x, y, and z directions (e.g., generated by gradient coil 202) with specific time, frequency, and phase can be superimposed on the uniform magnetic field. This allows the RF excitation signal to excite H atoms in the desired slice within the patient's body, encoding unique phase and frequency information in the MR signal based on the position of the hydrogen atoms in the "image slice." Typically, the image portion of the patient's body is scanned through a series of measurement cycles, where the RF excitation signal and magnetic field gradients Gx, Gy, and Gz vary according to the MRI imaging protocol being used. Protocols can be designed for one or more tissues to become images, diseases, and / or clinical scenarios. Protocols can include a number of pulse sequences oriented in different planes and / or different parameters. Pulse sequences can include spin echo sequences, gradient echo sequences, diffusion sequences, inversion recovery (IR) sequences, etc., or any combination thereof. For example, a spin echo sequence may include Fast Spin Echo (FSE), Turbine Spin Echo (TSE), Fast Acquisition with Relaxation Enhancement (RARE), Half Fourier Acquisition Single Turbine Spin Echo (HASTE), Turbine Gradient Spin Echo (TGSE), or any combination thereof. The protocol may also include information about image contrast and / or ratio, ROI, slice thickness, image type (e.g., T1-weighted image, T2-weighted image, proton density-weighted image, etc.), T1, T2, echo type (spin echo, Fast Spin Echo (FSE), Fast Recovery FSE, Single FSE, Gradient Backtrack Echo, Fast Image with Steady-State Motion, etc.), flip angle value, acquisition time (TA), echo time (TE), repetition time (TR), echo chain length (ETL), number of phases, number of excitations (NEX), inversion time, bandwidth (e.g., RF receiver bandwidth, RF transmitter bandwidth, etc.), or any combination thereof.

[0073] Figure 3 This is a schematic diagram of exemplary hardware and / or software components of a computing device 300 according to some embodiments of this specification. The computing device 300 can be used to implement any component of the MRI system 100 as described herein. For example, processing device 120 and / or terminal 140 can be implemented on the computing device 300 respectively through their hardware, software programs, firmware, or combinations thereof. Although only one such computing device is shown for convenience, the computer functions associated with the MRI system 100 described herein can be implemented in a distributed manner on multiple similar platforms to distribute the processing load. Figure 3 As shown, the computing device 300 may include a processor 310, a memory 320, an input / output (I / O) 330, and a communication port 340.

[0074] Processor 310 can execute computer instructions (program code) and perform the functions of processing device 120 according to the techniques described herein. Computer instructions may include routines, programs, objects, components, signals, data structures, procedures, modules, and functions that perform the specific functions described herein. For example, processor 310 can process image data acquired from MRI scanner 110, terminal 140, storage device 130, and / or any other component of MRI system 100.

[0075] For illustrative purposes only, only one processor is described in the computing device 300. However, it should be noted that the computing device 300 in this specification may also include multiple processors, and therefore the operations of the methods described herein, which are executed by one processor, may also be executed jointly or individually by multiple processors. For example, if both operations A and B are executed in the processor of the computing device 300 in this specification, it should be understood that operations A and B may also be executed jointly or individually by two different processors in the computing device 300 (e.g., the first processor executes operation A, the second processor executes operation B, or the first and second processors jointly execute operations A and B).

[0076] The memory 320 may store data / information acquired from the MRI scanner 110, terminal 140, storage device 130, and / or any other component of the MRI system 100. In some embodiments, the memory 320 may store one or more programs and / or instructions to perform the exemplary methods described herein. For example, the memory 320 may store a program for processing device 120 to perform SMS imaging.

[0077] I / O 330 can input and / or output signals, data, information, etc. In some embodiments, I / O 330 allows a user to interact with processing device 120. In some embodiments, I / O 330 may include input devices and output devices. Input devices may include alphanumeric keys and other keys, and can be input via a keyboard, touchscreen (e.g., with haptic or haptic feedback), voice input, eye-tracking input, brain monitoring system, or any other similar input mechanism. Input information received through the input devices may be transmitted, for example, via a bus to another component (e.g., processing device 120) for further processing.

[0078] Communication port 340 can be connected to a network (e.g., network 150) to facilitate data communication. Communication port 340 can establish a connection between processing device 120 and MRI scanner 110, terminal 140 and / or storage device 130.

[0079] Figure 4This is a schematic diagram of exemplary hardware and / or software components of a mobile device 400 according to some embodiments of this specification. In some embodiments, one or more components of the MRI system 100 (e.g., terminal 140 and / or processing device 120) may be implemented on the mobile device 400.

[0080] like Figure 4 As shown, the mobile device 400 may include a communication platform 410, a display 420, a graphics processing unit (GPU) 430, a central processing unit (CPU) 440, an input / output 450, memory 460, and a storage 490. In some embodiments, any other suitable components, including but not limited to a system bus or controller (not shown), may also be included in the mobile device 400. In some embodiments, an operating system 470 (e.g., iOS™, Android™, Windows Phone™) and one or more applications 480 may be loaded from storage 490 into memory 460 for execution by CPU 440. Application 480 may include a browser or any other suitable mobile application for receiving and presenting information related to the MRI system 100. User interaction with the information flow may be implemented via input / output 450 and provided via network 150 to processing device 120 and / or other components of the MRI system 100.

[0081] To implement the various modules, units, and functions described in this specification, a computer hardware platform can be used as the hardware platform for one or more of the components described herein. A computer with user interface components can be used to implement a personal computer (PC) or any other type of workstation or terminal device. If properly programmed, a computer can also act as a server.

[0082] Figure 5 This is a block diagram of an exemplary processing device 120 according to some embodiments of this specification. Figure 5 As shown, the processing device 120 may include a control module 501, an aliased image reconstruction module 502, a reference image generation module 503, a layer image reconstruction module 504, an acquisition module 505, and a quantitative measurement module 506.

[0083] Control module 501 can be configured to control one or more components of MRI system 100. For example, during each frame in at least two frames (or more frames), control module 501 can be configured to cause the MRI scanner to apply at least two (or more) PE steps to each of at least two (or more) slice locations of an object (e.g., a patient) to acquire a set of echo signals. As used herein, a slice location of an object can refer to a cross-section of the object parallel to the XY plane defined by coordinate system 160. A frame can refer to a time period of any duration. A PE step can refer to a single acquisition step for spatial encoding along a phase encoding direction. In some embodiments, during each of at least some PE steps in each frame, a phase modulation gradient can be applied, for example, by the Z-coil of the MRI scanner along the slice encoding direction. Further description of the acquisition of echo signals can be found elsewhere in this specification. See, for example, [link to documentation]. Figure 6 Step 601 and its related description.

[0084] The aliased image reconstruction module 502 can be configured to reconstruct an aliased image representing at least two(multiple) layer locations of objects in a frame based on a set of echo signals acquired in the frame. For example, the aliased image reconstruction module 502 can sample the echo signals acquired in the frame and store the sampled data in a k-space matrix. The aliased image reconstruction module 502 can further reconstruct the k-space matrix into an aliased image of the frame by performing a Fourier transform. Further description of the reconstruction of aliased images can be found elsewhere in this specification. For example, see... Figure 6 Step 602 and its related description.

[0085] The reference image generation module 503 can be configured to generate at least two reference layer images based on at least two aliased images. A reference layer image is an image representing one of at least two (or more) layer locations in one or more frames across at least two frames (or more frames). In some embodiments, the reference layer image can be generated by combining (e.g., linearly combining) at least two aliased images from the aliased images of a frame. Further description of the generation of reference images can be found elsewhere in this specification. For example, see... Figure 6 Step 603 and its related description.

[0086] The layer image reconstruction module 504 can be configured to reconstruct at least one layer image based on the aliased image and a reference layer image. Each layer in the at least one layer image can represent a layer location in one of the frames. In some embodiments, at least one layer image can be reconstructed based on the aliased image and the reference layer image according to a parallel imaging reconstruction algorithm. Further description of layer image reconstruction can be found elsewhere in this specification. For example, see... Figure 6 Step 604 and its related description.

[0087] The acquisition module 505 can be configured to acquire information related to the MRI system 100. For example, the acquisition module 505 can acquire at least two sets of undersampled k-space data corresponding to at least two frames (or more frames). Each set of undersampled k-space data can be acquired simultaneously from at least two (or more) slice locations of an object in one of the at least two frames (or more frames) using an MRI scanner. Depending on the sampling mode (e.g., pseudo-random sampling mode), a set of undersampled k-space data corresponding to a frame can be acquired in a frame using an MRI scanner. Further description of acquiring undersampled k-space data can be found elsewhere in this specification. For example, see... Figure 14 Step 1401 and its related description.

[0088] In some embodiments, the reference image generation module 503 can also be configured to reconstruct at least two reference layer images based on at least two sets of undersampled k-space data from at least two frames (or multiple frames). Each of the multiple reference layer images can represent a layer location in the multiple frames. For example, the reference image generation module 503 can generate at least two sets of reference k-space data based on the undersampled k-space data, and reconstruct at least two aliased images based on the reference k-space data. The reference image generation module 503 can further reconstruct reference layer images based on the aliased images. Further description of the generation of reference layer images can be found elsewhere in this specification. For example, see... Figure 15 And its related descriptions.

[0089] The layer image reconstruction module 504 can also be configured to reconstruct at least two (or more) image sequences based on at least two sets of undersampled k-space data and at least two reference layer images. Each of the at least two (or more) image sequences may correspond to a layer location and include at least two layer images of the corresponding layer location in the frame. For example, the layer image reconstruction module 504 may estimate at least two (or more) reconstruction parameters based on at least two reference layer images and reconstruct the image sequences by optimizing a cost function that includes at least some reconstruction parameters and at least two sets of undersampled k-space data. Further description of the reconstruction of image sequences can be found elsewhere in this specification. For example, see... Figure 14 Step 1403 and its related description.

[0090] In some embodiments, the acquisition module 505 may be configured to acquire at least two sets of k-space data corresponding to at least two frames (or more frames). An MRI scanner is used in one frame of the at least two frames (or more frames) to simultaneously acquire each of the at least two sets of k-space data from at least two (or more) slice locations of the object, with a waiting time following the application of a preparation pulse in that frame. In some embodiments, phase modulation may be applied to at least two (or more) slice locations in the at least two frames (or more frames) for inter-slice separation. In some embodiments, for each frame, the corresponding set of k-space data may be a set of fully sampled k-space data or a set of undersampled k-space data. Further description of acquiring at least two sets of k-space data corresponding to at least two frames (or more frames) can be found elsewhere in this specification. For example, see [link to documentation]. Figure 21 Step 2101 and its related description.

[0091] The quantitative measurement module 506 can be configured to perform quantitative measurements on an object based on at least two sets of k-space data acquired by the acquisition module 505. For example, the quantitative measurement module 506 can generate at least two quantitative maps of the layer location based on at least two sets of k-space data. The quantitative maps of the layer location can include the values ​​of quantitative parameters for each physical point of the layer location. In some embodiments, the quantitative measurements of the layer location can be... Figure 1 At least two target layer images are generated for the specified layer location. The target layer image can be a layer image for a single layer location. Further description of the generation of at least two quantitative maps for a layer location can be found elsewhere in this specification. For example, see [link to documentation]. Figure 21 Step 2102 and its related description.

[0092] It should be noted that the above description is for illustrative purposes only and is not intended to limit the scope of this specification. Various changes and modifications can be made by those skilled in the art based on the teachings of this specification. However, these changes and modifications do not depart from the scope of this specification. For example, the processing device 120 may include one or more additional modules, such as a storage module (not shown) for storing data. As another example, one or more modules of the processing device 120 described above may be omitted. Alternatively or optionally, two or more modules of the processing device 120, such as the aliased image reconstruction module 502 and the reference image generation module 503, may be integrated into a single component. The modules of the processing device 120 may be divided into two or more units.

[0093] Figure 6This is a flowchart illustrating an exemplary process for multi-slice simultaneous MRI according to some embodiments of this specification. In some embodiments, process 600 may be executed by MRI system 100. For example, process 600 may be implemented as a set of instructions (e.g., an application program) stored in a storage device (e.g., storage device 130, memory 320, and / or memory 490). In some embodiments, processing device 120 (e.g., processor 310 of computing device 300, CPU 440 of mobile device 400, and / or...) Figure 5 One or more modules shown can execute this set of instructions and can be instructed to execute process 600 accordingly.

[0094] In some embodiments, the executable process 600 is used to simultaneously image at least two(multiple) slice locations of an object (e.g., a patient, a specific organ of a patient, an artificial object) using an MRI scanner. As used herein, a slice location of the object may refer to a cross-section of the object (e.g., a plane parallel to the XY plane defined by coordinate system 160). The count of the imaging slice locations can be equal to any positive number, such as 2, 3, 4, 5, etc. The imaging slice locations can be located anywhere on the object. The MRI scanner used for simultaneous imaging may include […]. Figure 1 and 2 The MRI scanner 110 described herein may include one or more similar components. For example, the MRI scanner may include a main magnet, three sets of gradient coils, RF coils, etc., or any combination thereof. The three sets of gradient coils may be configured to generate gradient magnetic fields Gx, Gy, and Gz in the X, Y, and Z directions, respectively, as defined by coordinate system 160. For illustrative purposes, one of the at least two(multiple) slice locations may be considered a first slice location, while the other slice locations may be considered at least one second slice location. The first slice location may be any slice location selected from the at least two(multiple) slice locations. In some embodiments, the first slice location may be located via the isocenter of the MRI scanner.

[0095] In 601, during each frame in at least two frames (or more frames), the processing device 120 (e.g., the processing circuitry of the control module 501 or the processor 310) enables the MRI scanner to apply at least two (or more) PE steps to each of at least two (or more) slice locations of the object to obtain a set of echo signals.

[0096] As used herein, a frame can refer to a time period of any duration. At least two frames (or multiple frames) can be consecutive or discontinuous. Different frames may have the same duration or different durations. A PE step can refer to a single acquisition step used for spatial coding along the phase coding direction. Each PE step in a frame can acquire an echo signal from the excited layer location, wherein the acquired echo signal can be stored as a PE line in a single row of the k-space matrix corresponding to the frame. The k-space matrix corresponding to the frame can be a two-dimensional matrix having a Kx-axis along the frequency coding direction and a Ky-axis along the phase coding direction. The k-space matrix corresponding to the frame can be used to reconstruct the aliased image corresponding to the frame, as described in detail in step 602.

[0097] In some embodiments, the size of the k-space matrix corresponding to a specific frame may be associated with the resolution of the aliased image of the frame to be reconstructed. For example, to reconstruct an aliased image with a resolution of 256×128, a 256×128 k-space matrix may need to be generated. That is, 256 PE steps may need to be applied in the specific frame to fill the 256 PE lines of the k-space matrix. The duration of the specific frame may be determined based on the count (or number) of PE steps and the unit duration of each PE step. In some embodiments, the k-space matrices corresponding to at least two (or more) frames may have the same matrix size. PE lines located in the same row of the k-space matrices in different frames may be considered to be located at the same position in k-space. PE steps corresponding to PE lines located at the same position in k-space and applied to different frames may be considered to correspond to each other.

[0098] In some embodiments, multiple PE steps can be performed during a frame by applying a specific pulse sequence. For example, a first pulse sequence without an echo sequence can be applied. The first pulse sequence may include at least two(multiple) RF excitation pulses, and only one echo signal (i.e., data corresponding to a single PE line) can be acquired after each RF excitation pulse. Exemplary first pulse sequences without an echo sequence may include bSSFP and corrupted GRE pulse sequences, etc. In some embodiments, each RF excitation pulse in the first pulse sequence may be a multi-band RF pulse, which may be applied simultaneously with a slice selection gradient to simultaneously excite at least two(multiple) slice locations to be imaged.

[0099] As another example, a second pulse sequence with echo sequences can be applied within the frame to perform the corresponding PE step. The second pulse sequence can acquire at least two (or more) echo signals (i.e., data corresponding to at least two PE lines) after each single RF excitation pulse. Exemplary second pulse sequences with echo sequences may include EPI pulse sequences, FSE pulse sequences, etc. In some embodiments, different pulse sequences may be suitable for scanning different objects. For example, an EPI pulse sequence can be used to scan a patient's brain.

[0100] In 602, for each of at least two (or more) frames, the processing device 120 (e.g., the aliasing image reconstruction module 502, the processing circuit of the processor 310) can reconstruct the aliasing image representing at least two (or more) layer positions in the frame based on a corresponding set of echo signals.

[0101] In some embodiments, for each frame, the processing device 120 may sample a set of echo signals acquired in the frame and store the sampled data in the aforementioned k-space matrix corresponding to the frame. The processing device 120 may further reconstruct the k-space matrix corresponding to the frame into an aliased image of the frame by performing a Fourier transform. The reconstructed aliased image may include aliasing artifacts, i.e., aliased pixels. In order to reduce aliasing artifacts in the aliased image and promote interlayer separation based on the aliased image, it may be desirable that portions of the reconstructed aliased image corresponding to different layer positions of the object have a preset field of view (FOV) offset relative to each other in each reconstructed aliased image. For example, for an aliased image of two layer positions with a resolution of 128×128, it is desirable that portions of the aliased image corresponding to the two layer positions have a half FOV offset relative to each other, for example, an offset of 64 pixels along the phase encoding direction. As another example, for an aliased image of three layer locations with a resolution of 128×300, it is desirable that the portions of the aliased image corresponding to every two adjacent layer locations have a one-third FOV offset from each other, for example, an offset of 100 pixels along the phase encoding direction. In some embodiments, the preset FOV offset may be the default setting of the MRI system 100, or it may be manually set by the user of the MRI system 100 via, for example, a terminal (e.g., terminal 140). Alternatively, the processing device 120 may determine the preset FOV offset based on, for example, the count of the layer locations to be imaged, the distance between different layer locations, the sensitivity of the RF coil (e.g., RF coil 203) used for echo signal detection, or any combination thereof.

[0102] To achieve a predetermined FOV offset in the aliased image of a frame, at least two (or more) phase modulation gradients can be applied by the gradient coil (e.g., the Z-coil) of the MRI scanner along the layer encoding direction (i.e., the Z-direction of coordinate system 160) in the frame. For example, during each PE step (or a portion thereof) in the frame, after the excitation layer location and before the readout of the corresponding echo signal, the phase modulation gradients can be applied by the Z-coil of the MRI scanner along the layer encoding direction. Due to the phase modulation gradients applied in the PE step, each layer location can have a specific phase when the corresponding echo signal is acquired.

[0103] In some embodiments, the phase modulation gradient applied to the frame can be designed to avoid the need for additional reference scans of the layer positions. For example, for corresponding PE steps applied in a pair of frames (at least two frames, or more), the phase difference between the second layer position and the first layer position is different, where the pair of frames can be two consecutive or non-consecutive frames in at least two frames (or more). This is merely an example. Figure 7 As shown, during each first PE step in frames 1 and 2, a phase modulation gradient can be applied such that the phase difference between layer positions S1 and S2 changes from -90° in frame 1 to 90° in frame 2. As another example, such as... Figure 11 As shown, the phase modulation gradient can be applied during the first PE step in frame 3, such that the phase difference between layer positions S3 and S4 changes from -120° in frame 3 to 0° in frame 4, and the phase difference between layer positions S3 and S5 changes from -240° in frame 3 to 0° in frame 4.

[0104] In some embodiments, during at least one PE step in at least one frame, after the corresponding echo signal is read out, a compensating magnetic field gradient may be applied along the layer coding direction. The compensating magnetic field gradient may have the same amplitude and opposite gradient direction as the phase modulation gradient applied in the at least one PE step. This can eliminate or reduce the influence of the phase modulation gradient applied in the at least one PE step on the echo signal acquisition in the next PE step. In some embodiments, in each PE step where the phase modulation gradient is applied, the compensating magnetic field gradient may be applied after the corresponding echo signal is read out. For example, during a frame in which a bSSFP pulse sequence is applied, the compensating magnetic field gradient may be applied in each PE step of the frame. Alternatively, PE steps in a frame may be performed without a compensating magnetic field gradient, for example, in a frame in which a corrupted GRE pulse sequence is applied.

[0105] In some embodiments, a phase-modulated RF excitation pulse may be applied in at least one PE step within at least one frame to excite at least two(multiple) layer locations, and the phase modulation in the at least one PE step may be achieved by a combination of the phase-modulated RF excitation pulse and the phase modulation gradient applied to the at least one PE step. For example, to achieve a 180-degree phase difference between a second layer location and a first layer location in a PE step, a 90-degree phase difference may be achieved by the phase-modulated RF excitation pulse, and the remaining 90-degree phase difference by the phase modulation gradient. Further description of the configuration of the pulse sequence applied in a frame can be found elsewhere in this specification. For example, see... Figure 7-14 And related explanations.

[0106] In 603, the processing device 120 (e.g., the reference image generation module 503, the processing circuit of the processor 310) can generate at least two reference layer images based on at least two (or more) aliased images.

[0107] As used herein, a reference layer image refers to an image representing one of at least two (or more) layer locations across at least two (or more) frames. The temporal resolution of the reference layer image may be lower than that of the aliased image reconstructed in 602 and the layer image reconstructed in 604. For example, the aliased image may correspond to a single frame, while the reference layer image may be generated based on multiple aliased images, thus having a lower temporal resolution.

[0108] In some embodiments, a reference layer image can be generated by combining (e.g., linearly combining) at least two(more) of the aliased images reconstructed in 602. For example, four aliased images (including the first, second, third, and fourth aliased images) corresponding to four frames (including the first, second, third, and fourth frames) can be reconstructed in 602. A reference layer image for a specific layer location can be generated by combining at least two(more) of the four aliased images. As an example only, a reference layer image R1 for the first layer location can be generated by superimposing the first and second aliased images or subtracting the first aliased image from the second aliased image. The reference layer image R1 may correspond to the first and second frames and has a lower temporal resolution than the original four aliased images. As another example, the reference layer image R2 for the first layer location may be a weighted sum of the first, second, and third aliased images. The reference layer image R2 may correspond to the first, second, and third frames and has a lower temporal resolution than the original four aliased images. In some embodiments, the average of the reference layer images R1 and R2 can be determined as the final reference layer image for the first layer location.

[0109] In 604, processing device 120 (e.g., layer image reconstruction module 504, processing circuitry of processor 310) can reconstruct at least one layer image based on the aliased image and a reference layer image. Each of the at least one layer image can represent a layer position of at least two (or more) layer positions in one frame of at least two (or more) frames. The at least one layer image can have the same temporal resolution as the aliased image described in 602. As used herein, "based on aliased image and reference layer image" means "based on at least a portion of the aliased image and at least a portion of the reference layer image".

[0110] At least one layer of image reconstruction can be performed based on parallel imaging reconstruction algorithms (e.g., slice-generalized auto-calibrating partial parallel acquisition (GRAPPA), simultaneous acquisition of spatial harmonics (SMASH), sensitivity encoding (SENSE), etc.) and on the aliased image and reference layer image. In some embodiments, for each layer location in each frame, the corresponding layer image can be reconstructed in 604. By way of example only, if there are two layer locations and two frames, four layer images can be reconstructed. Alternatively, only a portion of the four layer images can be reconstructed in 604. By way of example only, in 604, a layer image of the first layer location in a frame can be reconstructed based on the aliased image of a frame and the reference layer image of the first layer location, according to the GRAPPA algorithm.

[0111] In some embodiments, the object may undergo physiological motion over at least a frame period. For example, the object may include the heart of a patient undergoing cardiac motion. At least two(multiple) layer locations in the patient's heart can be imaged to generate a series of layer images for each layer location in at least two(multiple) cardiac phases. For each layer location in the patient's heart, the corresponding layer images can dynamically illustrate cardiac motion at that layer location along the time dimension at different cardiac phases. In some embodiments, the object may undergo little or no physiological motion over at least two (multiple) frames. For example, the object may include the brain of a patient. At least two(multiple) layer locations in the patient's brain can be imaged to generate a series of layer images for each layer location. For each layer location in the patient's brain, the corresponding layer images can dynamically illustrate changes in activated regions of the brain (e.g., changes in blood flow).

[0112] It should be noted that the above description of process 600 is for illustrative purposes only and is not intended to limit the scope of this specification. Various changes and modifications can be made by those skilled in the art based on the teachings of this specification. However, these changes and modifications do not depart from the scope of this specification. In some embodiments, process 600 may be performed by one or more additional steps not described and / or by omitting one or more of the steps described above. For example, process 600 may include an additional step of sending layer images to a terminal device (e.g., a doctor's terminal device 140) for display. In some embodiments, two or more steps of process 600 may be integrated into a single step, and / or a single step of process 600 may be divided into two steps. By way of example only, steps 602 to 604 may be integrated into a single step, wherein processing device 120 may reconstruct layer images based on at least two sets of echo signals acquired in 601. In some embodiments, a single reference layer image of a specific layer location may be generated in 603 to reconstruct a layer image of that specific layer location in 604.

[0113] Figure 7 This is a schematic diagram illustrating an exemplary bSSFP pulse sequence 700 according to some embodiments of this specification. The bSSFP pulse sequence 700 can be applied by an MRI scanner (e.g., MRI scanner 110) to simultaneously image slice location S1 and slice location S2 of a subject. Figure 7 As shown, the bSSFP pulse sequence 700 can be applied in frames 1 and 2 with different modulation mechanisms. During each frame period in frames 1 and 2, at least two (or more) PE steps (e.g., as shown) are applied. Figure 7 The PE1, PE2, PE3 and PE4 shown can be applied to layer positions S1 and S2 to obtain a corresponding set of echo signals.

[0114] For illustrative purposes, the application of the bSSFP pulse sequence 700 in frame 1 is described below as an example. In each PE step of frame 1, an excitation RF pulse (e.g., a multi-band RF pulse) can be applied simultaneously with a layer selection gradient to simultaneously excite layer positions S1 and S2, and echo signals can be acquired from layer positions S1 and S2. The echo signals acquired in each PE step of frame 1 can be stored as PE lines in a k-space matrix corresponding to frame 1. The aliased image A1 corresponding to layer positions S1 and S2 of frame 1 can be reconstructed by performing a Fourier transform on the k-space matrix corresponding to frame 1.

[0115] In some embodiments, during each PE step in frame 1, after excitation of layer positions S1 and S2 and before readout of the corresponding echo signals, a phase modulation gradient may be applied by the Z-coil of the MRI scanner to impart a predetermined FOV / 2 shift between the portions corresponding to layer positions S1 and S2 in the aliased image A1. For example, layer position S1 may be located at the isocenter of the MRI scanner, and the phase of layer position S1 in different PE steps in frame 1 may always be equal to 0°. Due to the phase modulation gradient applied in the PE steps of frame 1, the phase of layer position S2 may alternate between -90° and 90° along the phase encoding direction, and the phase difference between layer positions S1 and S2 may alternate between 90° and -90° along the phase encoding direction. In some embodiments, the intensity of the phase modulation gradient applied in the PE steps may be determined based on a predetermined FOV shift, the distance between layer positions S1 and S2, the gyromagnetic ratio of the object, the amplitude of the phase modulation gradient, the duration of the phase modulation gradient, etc., or any combination thereof. For example, the minimum value of the gradient moment Mz of the phase modulation gradient can be equal to φ / γd, where φ refers to the phase difference between layer positions S1 and S2 introduced by the phase modulation gradient, γ refers to the gyromagnetic ratio, and d refers to the distance between layer positions S1 and S2.

[0116] Ideally, in the PE step of frame 1, the phase modulation of layer positions S1 and S2 can be adjusted to 0 after the readout of the corresponding echo signals and before the next excitation of layer positions S1 and S2, in order to eliminate or reduce the influence of the phase modulation gradient on the acquisition of the echo signals in the next PE step. To this end, in some embodiments, after the readout of the corresponding echo signals, a compensating magnetic field gradient (or prephasing gradient lobe) can be applied along the layer coding direction in the PE step of frame 1 to maintain overall gradient balance, i.e., no net zerothmoment. The compensating magnetic field gradient applied in the PE step can have the same amplitude as the phase modulation gradient (or rephasing gradient lobe) applied in the PE step but with the opposite gradient direction. For example, in a particular PE step of frame 1, after the phase modulation gradient is applied, the phase of layer position S2 is equal to -90°. After the corresponding echo signal is read out and before the next excitation RF pulse is applied, a compensating magnetic field gradient can be applied to change the phase of layer position S2 by 90° to 0°.

[0117] The application of the bSSFP pulse sequence 700 in frame 2 can be similar to the application of the bSSFP pulse sequence 700 in frame 1, except that the phase modulation gradient applied in each PE step of frame 2 can be different, so that the phase difference between layer positions S1 and S2 is different for the corresponding PE steps in frame 1 and frame 2. This is just an example. Figure 7 As shown, the phase of layer position S2 in frame 2 alternates between 90° and -90° along the phase coding direction, and the phase difference between layer positions S1 and S2 in frame 2 can alternate between -90° and 90° along the phase coding direction. For a PE step corresponding to the PE line at the same position in k-space and applied in frames 1 and 2, the phase difference between layer positions S1 and S2 can vary by 180°. Taking the first PE step applied in frames 1 and 2 as an example, the phase difference between layer positions S1 and S2 changes from -90° in frame 1 to 90° in frame 2.

[0118] In some embodiments, the processing device 120 can, for example, perform step 602 to reconstruct an aliased image A1 corresponding to layer positions S1 and S2 of frame 1 based on the echo signals acquired in frame 1, and an aliased image A2 corresponding to layer positions S1 and S2 of frame 2 based on the echo signals acquired in frame 2. Due to phase modulation in frames 1 and 2, the aliased image A1 can be considered as the sum of layer positions S1 and S2, and the aliased image A2 can be considered as the difference between layer positions S1 and S2. The aliased images A1 and A2 can be represented by equations (1) and (2), respectively, as follows:

[0119] A1=S1+S1, (1)

[0120] A2 = S1 - S2. (2)

[0121] The reference layer image F1 representing layer position S1 in frame 1 and frame 2 and the reference layer image F2 representing layer position S2 in frame 1 and frame 2 can be determined by linearly combining the aliased images A1 and A2 according to equations (3) and (4), as shown below:

[0122]

[0123]

[0124] The temporal resolution of reference layer images F1 and F2 may be lower than that of aliased images A1 and A2. Processing device 120 can also reconstruct one or more layer images of layer positions S1 and S2 based on aliased images A1 and A2 and reference layer images F1 and F2. For example, processing device 120 can reconstruct the layer image of each layer position in layer positions S1 and S2 in frame 1 using a parallel imaging reconstruction algorithm based on aliased image A1, reference layer image F1, and reference layer image F2. Similarly, processing device 120 can reconstruct the layer image of each layer position in layer positions S1 and S2 in frame 2 based on aliased image A2, reference layer image F1, and reference layer image F2.

[0125] In some embodiments, Figure 7The bSSFP pulse sequence 700 shown can be applied to slice locations S1 and S2 in a patient's heart for use in SMS cardiac MRI. For illustrative purposes, FIG8A is an exemplary aliased image 810 of slice locations S1 and S2 in the heart acquired in frame 1, according to some embodiments of this specification. FIG8B is an exemplary aliased image 820 of slice locations S1 and S2 in the heart acquired in frame 2, according to some embodiments of this specification. FIG9A is an exemplary reference slice image 910 of slice location S1 in frames 1 and 2, according to some embodiments of this specification. FIG9B is an exemplary reference slice image 920 of slice location S2 in frames 1 and 2, according to some embodiments of this specification. Figure 10 The exemplary layer image 1010 of layer position S1 in frame 1, the exemplary layer image 1020 of layer position S2 in frame 1, the exemplary layer image 1030 of layer position S1 in frame 2, and the exemplary layer image 1040 of layer position S2 in frame 2 are shown according to some embodiments of this specification.

[0126] Figure 11 This is a schematic diagram of an exemplary bSSFP pulse sequence 1100 according to some embodiments of this specification. The bSSFP pulse sequence 1100 can be applied by an MRI scanner (e.g., MRI scanner 110) to simultaneously image slice locations S3, S4, and S5. Figure 11 As shown, the bSSFP pulse sequence 1100 can be applied in frames 3, 4, and 5 with different modulation mechanisms. It should be noted that the terms "layer position Sn" and "frame n" are used herein for ease of description, not for limitation. For example, frame 3 can be... Figure 7 The frame may be the same as or different from frame 1. As another example, layer position S3 may be the same as... Figure 7 The layer positions S1 are the same or different.

[0127] The application of the bSSFP pulse sequence 1100 in the frame can be similar to... Figure 7The application of the bSSFP pulse sequence 700 within a frame can differ from the phase modulation applied to the bSSFP pulse sequence 1100, except that the phase modulation of the bSSFP pulse sequence 700 can be different. Taking frame 3 as an example, after excitation layer positions S3, S4, and S5 and before the corresponding echo signal is read out, a phase modulation gradient can be applied in each of the first, third, fourth, and sixth PE steps, etc. Due to the phase modulation gradient applied in frame 3, the phase at layer position S4 can periodically change from -120° to 0° and then back to 120° along the phase coding direction, and the phase difference between layer positions S3 and S4 can periodically change from -120° to 0° and then back to 120° along the phase coding direction in frame 3. The phase of layer position S5 can periodically change from -240° to 0° and then back to 240° along the phase encoding direction, and the phase difference between layer positions S3 and S5 can periodically change from -240° to 0° and then back to 240° along the phase encoding direction in frame 3. The phase modulation gradient applied in frame 3 can impart a preset FOV / 3 offset between adjacent layers in the aliased image A3 corresponding to frame 3, which is reconstructed based on the signal acquired in frame 3.

[0128] The application of the bSSFP pulse sequence 1100 in frames 4 and 5 can be similar to the application of the bSSFP pulse sequence 1100 in frame 3, except that the phase modulation gradients applied in the three frames can be different. Thus, for corresponding PE steps in a pair of frames 3, 4, and 5, the phase difference between layer positions S3 and S4 can be different, and / or the phase difference between layer positions S3 and S5 can be different. As an example only, the phase difference between S3 and S4 in the first PE step of frame 3 can be equal to -120°, which becomes 0° in the first PE step of frame 4 and 120° in the first PE step of frame 5. As another example, the phase difference between S3 and S5 in the first PE step of frame 3 can be equal to -240°, which becomes 0° in the first PE step of frame 4 and 240° in the first step of frame 5.

[0129] In some embodiments, the processing device 120 can reconstruct an aliased image A3 corresponding to layer positions S3, S4, and S5 of frame 3 based on the echo signals acquired in frame 3, an aliased image A4 corresponding to layer positions S3, S4, and S5 of frame 4 based on the echo signals acquired in frame 4, and an aliased image A5 corresponding to layer positions S3, S4, and S5 of frame 5 based on the echo signals acquired in frame 5. Due to phase modulation in frames 3, 4, and 5, the aliased images A3, A4, and A5 can be represented by equations (5), (6), and (7), respectively, as follows:

[0130] A3 = S3 + S4 + S5, (5)

[0131]

[0132]

[0133] According to equations (8), (9), and (10), the reference layer image F3 representing layer position S3 in frames 3 to 5, the reference layer image F4 representing layer position S4 in frames 3 to 5, and the reference layer image F5 representing layer position S5 in frames 3 to 5 can be determined by linearly combining the aliased images A3, A4, and A5, as shown below:

[0134]

[0135]

[0136]

[0137] The reference layer images F3, F4, and F5 may have a lower temporal resolution than the aliased images A3, A4, and A5. The processing device 120 can also reconstruct one or more layer images of layer positions S3, S4, and S5 based on the aliased images A3 to A5 and the reference layer images F3 to F5. For example, the processing device 120 can reconstruct layer images for each of the layer positions S3, S4, and S5 in frame 3 based on the aliased image A3 and the reference layer images F3, F4, and F5.

[0138] Figure 12 This is a schematic diagram of an exemplary FSE pulse sequence 1200 according to some embodiments of this specification. The FSE pulse sequence 1200 can be applied by an MRI scanner (e.g., MRI scanner 110) to simultaneously image slice location S6 and slice location S7 of a subject. Figure 12 As shown, the FSE pulse sequence 1200 can be applied in frames 6 and 7 with different modulation mechanisms. During each frame in frames 6 and 7, multiple PE steps can be performed and the corresponding echo signal sequence can be obtained after a single RF excitation pulse using a series of 180° refocusing pulses.

[0139] Similar to combination Figure 7 The bSSFP pulse sequence 700 can apply a phase modulation gradient during each PE step in frames 6 and 7, such that the phase difference between layer positions S6 and S7 varies by 180° in the corresponding PE steps in frames 6 and 7, as shown below. Figure 12As shown. After reading the corresponding echo signal and before the next PE step, it may be necessary to apply a compensating magnetic field gradient in each PE step of frames 6 and 7. In some embodiments, the processing device 120 may reconstruct one or more layer images of layer locations S6 and S7 based on the echo signals acquired in frames 6 and 7. The reconstruction of the layer images of layer locations S6 and S7 may be similar to... Figure 7 The method of reconstructing the layer images at layer positions S1 and S2 is described above and will not be repeated here.

[0140] Figure 13 This is a schematic diagram illustrating an exemplary EPI pulse sequence 1300 according to some embodiments of this specification. The EPI pulse sequence 1300 can be applied by an MRI scanner (e.g., MRI scanner 110) to simultaneously image slice locations S8 and S9 of a subject. Figure 13 As shown, the EPI pulse sequence 1300 can be applied in frames 8 and 9 with different modulation mechanisms. During each frame in frames 8 and 9, multiple echoes of different PE steps can be obtained by using a rephase gradient after a single RF excitation pulse.

[0141] and Figure 7 Similar to the bSSFP pulse sequence 700, a phase modulation gradient can be applied during each PE step in frames 8 and 9, such that the phase difference between layer positions S8 and S9 varies by 180° in the corresponding PE steps of frames 8 and 9, as shown below. Figure 13 As shown. After reading the corresponding echo signal and before the next PE step, it may be necessary to apply a compensating magnetic field gradient in each PE step in frames 8 and 9. In some embodiments, the processing device 120 may reconstruct one or more layer images of layer locations S8 and S9 based on the echo signals acquired in frames 8 and 9. The reconstruction of the layer images of layer locations S8 and S9 may be similar to Figure 7 The method of reconstructing the layer images at layer positions S1 and S2 is described above and will not be repeated here.

[0142] It should be noted that, such as Figure 7 , 11The exemplary pulse sequences shown in Figures 12 and 13, and their descriptions, are for illustrative purposes only and are not intended to limit the scope of this specification. Various changes and modifications can be made by those skilled in the art based on the teachings of this specification. However, these changes and modifications do not depart from the scope of this specification. In some embodiments, the phase modulation of a specific layer location in a particular PE step can be different from any other value shown in the figures. Furthermore, phase modulation in a particular PE step can be achieved alone by the phase modulation gradient as described above or by a combination of the phase modulation gradient as described above and the phase modulation RF excitation pulse. Furthermore, the equations provided above are illustrative examples and can be modified in various ways. For example, at least two aliased images of at least two frames (or more frames) can be reconstructed, and a reference layer image for a specific layer location can be generated based on any two or more of the aliased images.

[0143] Figure 14 This is a flowchart illustrating an exemplary process for multi-slice simultaneous MRI according to some embodiments of this specification. In some embodiments, process 1400 may be performed by MRI system 100. For example, process 1400 may be implemented as a set of instructions (e.g., an application program) stored in a storage device (e.g., storage device 130, memory 320, and / or memory 490). In some embodiments, processing device 120 (e.g., processor 310 of computing device 300, CPU 440 of mobile device 400, and / or...) Figure 5 One or more modules shown can execute this set of instructions and can be instructed to execute process 1400 accordingly.

[0144] In 1401, the processing device 120 (e.g., the interface circuit of the acquisition module 505 and the processor 310) can acquire at least two sets of undersampled k-space data corresponding to at least two frames (multiple frames).

[0145] An MRI scanner (e.g., MRI scanner 110) can be used to simultaneously acquire each of at least two sets of undersampled k-space data from at least two (or more) slice locations of an object in one of at least two (or more) frames. For example... Figure 6 The layer position of an object refers to its cross-section. A frame refers to a time period of any duration.

[0146] In some embodiments, a set of undersampled k-space data can be acquired by instructing an MRI scanner to perform an MR scan on an object (e.g., a patient or a portion thereof). The MR scan may include at least two frames (or more frames). During each of the at least two frames (or more frames), the MRI scanner may be instructed to apply multiple PE steps to at least two (or more) slice locations to acquire a set of echo signals, and each acquired echo signal may be stored as a PE line in a single row of a k-space matrix corresponding to that frame. Typically, it may be necessary to acquire full k-space data for the slice locations within a frame to reconstruct a full MR image corresponding to the slice locations of that frame. To accelerate data acquisition and reduce scan time, undersampling can be performed using methods such as reducing the number (or count) of k-space sampling steps, reducing the number (or count) of samples per row, reducing the number of lines per leaf (e.g., a set of parallel EP lines), reducing the number of leaves acquired per acquisition (or count), or any combination thereof, to acquire a portion of the full k-space data (i.e., a set of undersampled k-space data corresponding to that frame). In some embodiments, a set of undersampled k-space data may be pre-acquired and stored in a storage device (e.g., storage device 130, memory 320, memory 490, and / or external storage device). Processing device 120 may access the storage device and acquire a set of undersampled k-space data. Alternatively, processing device 120 may acquire information related to a set of echo signals acquired in a frame from the storage device and generate a set of undersampled k-space data for that frame based on the acquired information.

[0147] In some embodiments, depending on the sampling mode, an MRI scanner can be used to collect a set of undersampled k-space data corresponding to a frame. The sampling mode can specify a sampling trajectory along which multiple sampling points are acquired in the frame (forming one or more PE lines). The sampling modes corresponding to different frames can be the same or different. In some embodiments, a random sampling mode, such as a pseudo-random sampling mode, can be used in at least one of at least two (or more) frames. The pseudo-random sampling mode can be used to randomly acquire PE lines in at least one frame. Optionally, at least two (or more) pseudo-random values ​​can be generated according to the pseudo-random sampling mode, which are distributed according to a given probability distribution, and PE lines corresponding to the pseudo-random values ​​can be acquired. For example, the pseudo-random sampling mode can be designed according to the Latin hypercube algorithm.

[0148] In some embodiments, for a pair of adjacent frames in at least two frames (or more frames), their corresponding sampling modes may be different and / or interleaved. For example, a first sampling mode for acquiring odd-numbered PE lines may be used in each odd-numbered frame, and a second sampling mode for acquiring even-numbered PE lines may be used in each even-numbered frame. In some embodiments, the k-space data of the frame in matrix form (or simply the k-space matrix) may be divided into multiple regions with the same sampling density (measured by, for example, the count of sampling points in a unit region) or different sampling densities. For example, the k-space data may be fully sampled in one or more specific regions (e.g., the central region of the k-space matrix), while the k-space data may be undersampled in other regions. Optionally, the sampling density of one or more specific regions may be higher than the sampling density of other regions.

[0149] In some embodiments, to achieve automated calibration of multi-band imaging, the phase of at least one layer location can be modulated during the scanning of the object. By way of example only, the layer locations to be imaged simultaneously may include a first layer location and at least one second layer location. During each frame (or a portion thereof), the first layer location may be scanned without phase modulation, and at least one second layer location (or a portion thereof) may be scanned with phase modulation. Phase modulation of the second layer location within a frame may include phase modulation along the spatial dimension and / or phase modulation along the temporal dimension.

[0150] As used herein, spatial dimension refers to the phase coding dimension in k-space. Applying phase modulation along the spatial dimension of a frame to a second-layer location means modulating the phase of the second-layer location during each PE step (or a portion thereof) of the frame, such that the phase of the second-layer location varies along the phase coding direction in the frame. In some embodiments, the phase of the second-layer location can be modulated along the spatial dimension of the frame according to the frame's phase modulation mechanism before acquiring a set of undersampled k-space data corresponding to the frame. The frame's phase modulation mechanism can specify how the phase of the second-layer location is modulated along the phase coding dimension during the frame. For example, refer to... Figure 13 The phase of layer position S9 can be modulated during each PE step in frame 8 according to a specific phase modulation mechanism, and alternates between -90° and 90° along the phase coding direction.

[0151] In some embodiments, for the second layer position, the phase modulation mechanism of the frame can be specifically designed to achieve a preset FOV offset between the portions corresponding to the second layer position and the first layer position in the reconstructed aliased image of the frame. For example, in the frame, the phase of the first layer position can always be equal to 0°, and the phase of the second layer position can alternate between 0° and 180° along the phase coding direction, thereby achieving a preset FOV / 2 offset between the portions corresponding to the layer positions S' and S in the aliased image. In some embodiments, the phase modulation mechanism of the second layer position in the frame can be implemented by various phase modulation techniques described elsewhere in this specification (e.g., step 602 and its related description), such as phase-modulated RF excitation pulses, magnetic field gradients (e.g., phase-modulated gradients along the layer coding direction), compensated magnetic field gradients, etc., or any combination thereof.

[0152] In some embodiments, the phase of the second-layer position can be modulated along the time dimension, such that the phase modulation mechanisms of a pair of adjacent frames (at least two frames, or more) are different. For example, this pair of adjacent frames may include a first frame and a second frame following the first frame. Due to the phase modulation along the time dimension, different phase modulation mechanisms can be applied in the first and second frames, such that in the corresponding PE steps applied in the first and second frames, the phase of the second-layer position changes by a global phase offset from the first frame to the second frame. The global phase offset refers to the phase difference between the corresponding PE steps applied in the pair of adjacent frames. The global phase offset can be any positive value in the range of 0° to 360°. The global phase offsets for different second-layer positions can be the same or different.

[0153] In some embodiments, at least two (or more) layer locations may include N layer locations, and the global phase offset may be (360 / N) degrees. N may be a positive integer. For example, N may be equal to 2, meaning two layer locations are scanned simultaneously in a frame, and the global phase offset may be 180°. (See reference...) Figure 13 In frame 8, the phase of layer position S9 can be modulated along the spatial dimension according to the first phase modulation mechanism, alternating between -90° and 90°. The phase of layer position S9 is also modulated along the temporal dimension, which results in a second phase modulation mechanism corresponding to frame 9 that differs from the first phase modulation mechanism. According to the second phase modulation mechanism, the phase of layer position S9 alternates between 90° and -90° along the spatial dimension in frame 9. In the corresponding PE steps applied in frames 8 and 9, the phase of layer position S9 changes by 180°, that is, the global phase offset of layer position S9 is 180°. For example, refer to... Figure 11In the corresponding PE steps of frames 3 and 4, the layer position S4 changes by 120°, that is, the global phase offset of the layer position S4 is 120°; in the corresponding PE steps of frames 3 and 4, the layer position S5 changes by 240°, that is, the global phase offset of the layer position S5 is 240°.

[0154] It should be noted that the above description of phase modulation at at least one layer location is provided for illustrative purposes only and is not intended to limit the scope of this specification. Various variations and modifications can be made by those skilled in the art based on the teachings of this specification. For example, the phase of each layer location (including the first and second layer locations) can be modulated during MR scanning. As another example, the phase of the layer location can be modulated along one of the spatial and temporal dimensions. However, these variations and modifications do not depart from the scope of this specification.

[0155] In some embodiments, phase modulation applied to simultaneously excited layer locations (or a portion thereof) allows for self-calibrated multi-band imaging; that is, a single-band reference layer image can be extracted from an undersampled set of k-space data itself without additional reference scanning. Furthermore, the scanning process can be further accelerated by using compressed sensing techniques to acquire undersampled k-space data instead of fully sampled k-space data.

[0156] In 1402, the processing device 120 (e.g., the reference image generation module 503, the processing circuit of the processor 310) can reconstruct at least two reference layer images based on the set of undersampled k-space data of at least two frames (or more frames).

[0157] Each of the at least two reference layer images can represent a layer location within at least two frames (or more frames). The reference layer images can be non-aliased and have a lower temporal resolution than the layer images generated in step 1403 because they are generated based on undersampled k-space data from at least two frames (or more frames). In some embodiments, the processing device 120 can perform actions such as... Figure 15 The process 1500 includes one or more steps to reconstruct the reference layer image.

[0158] In 1403, the processing device 120 (e.g., the layer image generation module 504, the processing circuit of the processor 310) can reconstruct at least two (or more) image sequences based on the set of undersampled k-space data and at least two reference layer images.

[0159] Each image sequence in the image sequence can correspond to a layer location within a layer position and can include at least two rows of layer images for that corresponding layer location in a frame. For example, a patient's cardiac cycle can include 12 cardiac phases, and layer locations A and B in the patient's heart can be simultaneously imaged using ATOMICS as described above. An MR scan can include 12 or more frames covering the patient's 12 cardiac phases. Based on undersampled k-space data acquired during the scan, a sequence is generated as follows: Figure 20 Image sequence 2010 for layer position A and image sequence 2020 for layer position B are shown. Each image sequence in image sequences 2010 and 2020 includes 12 layer images corresponding to 12 cardiac phases at the corresponding layer position. The temporal resolution of image sequences 2010 and 2020 is equal to 2.88 × 15 milliseconds (ms), or 43.2 milliseconds. There are no obvious artifacts in image sequences 2010 and 2020, and the cardiac motion at layer positions A and B during the cardiac cycle is dynamically displayed by image sequences 2010 and 2020.

[0160] In some embodiments, to reconstruct an image sequence, processing device 120 may estimate multiple reconstruction parameters based on at least two reference layer images. For example, an MRI scanner may include at least two(multiple) receiver coils for echo signal detection, and the reconstruction parameters may include at least two(multiple) coil sensitivity maps of the receiver coils. In some embodiments, at least two coil images may be generated based on at least two reference layer images, where each coil corresponds to a single receiver coil. The coil images may be combined into a combined image according to, for example, a sum of squares (SOS) algorithm or an adaptive coil combination (ACC) algorithm. The coil sensitivity map of a particular receiver coil may be determined by dividing the corresponding coil image by the combined image. In some embodiments, for each of the at least two reference layer images, a set of coil sensitivity maps may be determined based on the reference layer images, thereby generating multiple sets of coil sensitivity maps corresponding to different reference layer images (i.e., different layer locations).

[0161] After estimating the reconstruction parameters, the processing device 120 can reconstruct the image sequence by optimizing a cost function, wherein the cost function may include at least some reconstruction parameters and a set of undersampled k-space data. Optionally, the cost function may also include a temporal total variation operator relating to the difference between images, which correspond to adjacent frames in each image sequence. In some embodiments, a first set of undersampled k-space data for a first frame may include some k-space data that is not included in a second set of undersampled k-space data for a second frame adjacent to the first frame. For example, the first set of undersampled k-space data may include odd-numbered PE lines, while the second set of undersampled k-space data may include even-numbered PE lines. The temporal total variation operator T may encourage information sharing between the first and second sets of undersampled k-space data in the image sequence reconstruction. For example, the temporal total variation operator T may use the odd-numbered PE lines of the first set of undersampled k-space data to fill the empty odd-numbered PE lines of the second set of undersampled k-space data. In some embodiments, the temporal total variation operator T may be used to apply a sparse transformation for L1 regularization. Sparse transformation can be performed based on one or more sparse transformation algorithms (such as Wavelet (WT) algorithm, Cosine (CT) algorithm, contourlet algorithm, curvelet algorithm, k-means singular value decomposition algorithm, Gabor algorithm, etc.) or any combination thereof.

[0162] For illustrative purposes, it is assumed that the layer locations to be imaged simultaneously include two layer locations (i.e., a first layer location and a second layer location), and an exemplary cost function (11) for reconstructing the image sequence x1 at the first layer location and the image sequence x2 at the second layer location is shown below:

[0163]

[0164] Where s1 refers to the coil sensitivity map determined based on the reference layer image at the first layer position, s2 refers to the coil sensitivity map determined based on the reference layer image at the second layer position, D refers to the k-space sampling operator, F refers to the Fourier transform operator, p1 refers to the phase modulation mechanism with respect to the first layer position in the frame, p2 refers to the phase modulation mechanism with respect to the second layer position in the frame, and λ refers to the indicator ‖Tx1‖ 1 and ||Tx2|| 1 The importance of regularization parameters, and T refers to the time total variation operator. Tx1 may be associated with the difference between the layer images corresponding to adjacent frames in image sequence x1. Tx2 may be associated with the difference between the layer images corresponding to adjacent frames in image sequence x2. The solution of x1 and x2 that minimizes the cost function (e.g., the cost function shown in equation (11)) can be used as the image sequence for the first and second layer positions.

[0165] It should be noted that the cost function (11) shown above is for illustrative purposes only and is not intended to limit the scope of this specification. For example, the cost function (11) may include one or more additional parameters. Alternatively or optionally, one or more parameters of the cost function (11), such as λ‖Tx1‖ 1 and / or λ‖Tx2‖ 1 , can be omitted.

[0166] It should be noted that the above description of process 1400 is for illustrative purposes only and is not intended to limit the scope of this specification. Various changes or modifications can be made by those skilled in the art based on the teachings of this specification. However, these changes and modifications do not depart from the scope of this specification. In some embodiments, process 1400 may be performed by one or more additional steps not described and / or by omitting one or more of the steps described above. For example, process 1400 may include the additional step of sending at least two (or more) image sequences to a diagnostic terminal device (e.g., a physician's terminal device 140).

[0167] Figure 15 This is a flowchart illustrating an exemplary process for reconstructing at least two reference layer images according to some embodiments of this specification. In some embodiments, one or more steps of process 1500 may be performed to achieve, Figure 14 At least a portion of step 1402.

[0168] In 1501, the processing device 120 (e.g., the reference image generation module 503, the processing circuit of the processor 310) can generate at least two sets of reference k-space data based on a set of undersampled k-space data corresponding to the frame.

[0169] In some embodiments, the processing device 120 can generate a set of reference k-space data by combining (e.g., linearly combining) undersampled k-space data corresponding to two or more frames. For example, a frame may include one or more odd-numbered frames and one or more even-numbered frames. Multiple sets of reference k-space data may include a first set of reference k-space data corresponding to odd-numbered frames and a second set of reference k-space data corresponding to even-numbered frames. The processing device 120 can generate the first set of reference k-space data based on one or more sets of undersampled k-space data corresponding to odd-numbered frames, and generate the second set of reference k-space data based on one or more sets of undersampled k-space data corresponding to even-numbered frames. In some embodiments, the first set of reference k-space data can be determined by averaging the set of undersampled k-space data corresponding to odd-numbered frames. Alternatively or optionally, the second set of reference k-space data can be determined by averaging the set of undersampled k-space data corresponding to even-numbered frames.

[0170] In step 1502, the processing device 120 (e.g., the reference image generation module 503, the processing circuitry of the processor 310) can reconstruct at least two aliased images based on at least two sets of reference k-space data. Each of the at least two aliased images can represent at least two (or more) layer positions in more than one frame of at least two (or more) frames.

[0171] In some embodiments, the processing device 120 can reconstruct at least two aliased images by performing Fourier transforms on at least two sets of reference k-space data. For example, the processing device 120 can reconstruct the aliased image corresponding to odd-numbered frames based on the first set of reference k-space data, and reconstruct the aliased image corresponding to even-numbered frames based on the second set of reference k-space data.

[0172] In 1503, the processing device 120 (e.g., the reference image generation module 503, the processing circuit of the processor 310) can generate at least two reference layer images based on at least two aliased images.

[0173] In some embodiments, step 1503 may be performed in a manner similar to step 603. For example, processing device 120 may generate a reference layer image by combining (e.g., linearly combining) at least two aliased images (or a portion thereof) reconstructed in 1502.

[0174] It should be noted that the above description of process 1500 is for illustrative purposes only and is not intended to limit the scope of this specification. Various changes and modifications can be made by those skilled in the art based on the teachings of this specification. However, these changes and modifications do not depart from the scope of this specification. In some embodiments, process 1500 may be performed by one or more additional steps not described and / or by omitting one or more of the steps described above. Alternatively or additionally, two or more steps (e.g., steps 1501 and 1502) may be integrated into a single step.

[0175] Figure 16 This is a schematic diagram of an exemplary phase modulation and undersampling mode 1600 in an MR scan according to some embodiments of this specification. MR scans can be performed to simultaneously image the first and second layer locations of an object. For example... Figure 16 As shown, an MR scan may include at least two (or more) odd-numbered frames and at least two (or more) even-numbered frames. A random undersampling mode is used in each of these at least two (or more) odd-numbered frames and at least two (or more) even-numbered frames. Figure 16The circular and cross icons represent a 180° and 0° phase difference between the first and second layer positions, respectively. In each odd-numbered frame, odd-numbered PE lines can have a 180° phase difference between the first and second layer positions, while even-numbered PE lines can have a 0° phase difference. In each even-numbered frame, odd-numbered PE lines can have a 0° phase difference between the first and second layer positions, while even-numbered PE lines can have a 180° phase difference.

[0176] In some embodiments, after acquiring a set of undersampled k-space data according to phase modulation and undersampling mode 1600, single-band reference layer images of the first and second layer positions can be generated based on the set of undersampled k-space data. For example, performing the following... Figure 17 The exemplary process is shown. (As shown in the example process.) Figure 17 As shown, a first set of reference k-space data K1 corresponding to odd-numbered frames can be determined based on the set of undersampled k-space data corresponding to odd-numbered frames; and a second set of reference k-space data K2 corresponding to even-numbered frames can be determined based on the set of undersampled k-space data corresponding to even-numbered frames. Then, the first set of reference k-space data K1 can be reconstructed into an aliased image A1′, representing the first and second layer positions in the odd-numbered frames. Due to the phase modulation applied to the odd-numbered frames, the aliased image A1′ can be considered as the sum of the first and second layer positions. Similarly, the second set of reference k-space data K2 can be reconstructed into an aliased image A2′, representing the first and second layer positions in the even-numbered frames. Due to the phase modulation applied to the even-numbered frames, the aliased image A2′ can be considered as the difference between the first and second layer positions. Furthermore, a reference layer image F1′ representing the first layer position and a reference layer image F2′ representing the second layer position can be determined by linearly combining the aliased images A1′ and A2′. The generation of the reference layer images F1′ and F2′ can be similar to... Figure 7 The method for generating reference layer images F1 and F2 is described above and will not be repeated here.

[0177] Figure 18 This is an exemplary phase modulation mechanism for the first and second layer positions in a frame, as shown in some embodiments of this specification. For example... Figure 18 As shown, the phase of the first layer position in different PE steps is always equal to 0°, and the phase of the second layer position is modulated along the phase coding direction. The phase difference between the first layer position and the second layer position is equal to 0° in each odd-numbered PE step. And equals in each even PE step In each PE step, before the corresponding echo signal is read out, the phase of the second-layer position is modulated by phase modulation gradient 1801 (or rephase gradient lobe), and after the corresponding echo signal is read out and before the next PE step, the total gradient of the second-layer position is balanced by compensating magnetic field gradient 1802 (or prephase gradient lobe). It should be understood that... Figure 18 The phase modulation mechanism described herein is provided for illustrative purposes only and is not intended to be limiting. Various modifications can be made to the phase modulation mechanism. For example, the first layer position can also be phase-modulated within the frame. As another example, phase modulation for the second layer position can be omitted in a portion of the PE step. As yet another example, the compensation magnetic field gradient 1802 can be omitted.

[0178] Figure 19 Layer images 1910, 1920, 1930, and 1940, corresponding to the same cardiac phase of the patient, are shown according to some embodiments of this specification. Layer images 1910 and 1920 correspond to one layer location of the patient's heart, and layer images 1930 and 1940 correspond to another layer location of the patient's heart. Layer images 1910 and 1930 are acquired simultaneously by scanning the patient using compressed sensing technology. Layer images 1920 and 1940 are acquired simultaneously by scanning the patient using the ATOMICS technology disclosed in this specification (e.g., according to process 1400). The cardiac morphology is described in each layer image from 1910 to 1940. Compared to using compressed sensing technology alone, the ATOMICS technology combines automatically calibrated multi-band imaging technology and compressed sensing technology, which can accelerate the scanning process without compromising image quality.

[0179] Figure 21 This is a flowchart of an exemplary process for generating at least two quantitative maps of at least two(multiple) slice locations, according to some embodiments of this specification. In some embodiments, process 2100 may be performed by MRI system 100. For example, process 2100 may be implemented as a set of instructions (e.g., an application program) stored in a storage device (e.g., storage device 130, memory 320, and / or memory 490). In some embodiments, processing device 120 (e.g., processor 310 of computing device 300, CPU 440 of mobile device 400, and / or...) Figure 5 One or more modules shown can execute this set of instructions and can be instructed to execute process 2100 accordingly.

[0180] In 2101, the processing device 120 (e.g., acquisition module 505) can acquire at least two sets of k-space data.

[0181] At least two sets of k-space data may correspond to at least two frames (or more frames). An MRI scanner can be used in one of the at least two frames (or more frames) to simultaneously acquire each of the at least two sets of k-space data from at least two (or more) slice locations of the subject, with a waiting time following the application of a preparation pulse in that frame. In other words, processing device 120 can use SMS imaging to acquire at least two sets of k-space data from at least two (or more) slice locations. SMS imaging may include at least two frames (or more frames). Each set of k-space data in the at least two sets may correspond to a waiting time following the application of a preparation pulse to at least two (or more) slice locations during SMS imaging. Figure 6 The layer position of an object refers to the cross-section of the object, and the frame refers to a time period of any duration.

[0182] As an example only, in a frame, a preparation pulse can be applied to the layer location of an object, followed by a specific wait time. After the wait time, a pulse sequence can be applied simultaneously to the layer location to perform at least two (or more) PE steps and acquire a corresponding set of k-space data. The preparation pulse can be used to acquire data for quantitative measurements of the layer location. Quantitative measurements can be used to determine one or more quantitative parameters of the layer location, such as T1, T2, lateral relaxation attenuation (T2*), signal attenuation rate (R2), lateral relaxation rate (R2*), etc., or any combination thereof. For example, to perform a T1 measurement at a layer location, a T1 preparation pulse (e.g., an IR pulse) can be used. As another example, to perform a T2 measurement at a layer location, a T2 preparation pulse can be used.

[0183] The frame wait time refers to the time interval between the preparation pulse and the first excitation pulse in the pulse sequence used for the PE step during the frame. For example, in T1 imaging, the wait time can also be referred to as the inversion time (TI) between the IR pulse and the 90-degree excitation pulse applied after the IR pulse. For T1 measurements to be performed, the wait times of at least two (or more) frames can be different. As used herein, at least two (or more) frames can be considered different if their wait times are partially or completely different.

[0184] In some embodiments, the wait time in a frame may be related to the location of the slice to be imaged. For example, a reference T1 for the slice location can be estimated based on the anatomical structure of the slice location. The TI values ​​for at least two (or more) frames may be manually set by a user (e.g., a physician) based on the reference T1, or automatically set by a computer device (e.g., processing device 120). For example, the TI values ​​for at least two (or more) frames may be 100 milliseconds (ms), 200 milliseconds, 350 milliseconds, etc. The pulse sequence applied after the wait time may include a GRE pulse sequence, an FSE pulse sequence, an EPI pulse sequence, a bSSFP pulse sequence, or any other suitable pulse sequence (e.g., such as...). Figure 2 The pulse sequence mentioned above.

[0185] In some embodiments, during SMS imaging for interlayer separation, phase modulation may be applied to one or more target layer-selection locations among at least two (or more) layer locations in the frame. As used herein, the target layer-selection location may also be referred to as a second layer location. The target layer-selection location may include all or a portion of the imaging layer locations.

[0186] In some embodiments, for each target layer location in each frame, the phase of the target layer location can be modulated along the spatial dimension (i.e., the phase coding dimension) according to the frame's phase modulation mechanism. For example, during a frame, the phase of the target layer location can be modulated such that the target layer location has different phases during the readout of different PE lines. The phase modulation applied to the target layer location along the spatial dimension can be used in the reconstructed aliased image of the frame to achieve a preset FOV offset between portions corresponding to different layer locations.

[0187] Additionally or alternatively, for each target layer selection location, the phase of the target layer selection location can be modulated along the time dimension, such that the phase modulation mechanisms of a pair of adjacent frames (at least two frames, or more) are different. For example, a pair of adjacent frames may include a first frame and a second frame following the first frame. Due to the phase modulation along the time dimension, different phase modulation mechanisms can be applied in the first and second frames, such that in the corresponding PE steps applied in the first and second frames, the phase of the target layer selection location changes with a global phase offset from the first frame to the second frame. In some embodiments, the phase modulation mechanism of the target layer selection location in a third frame following the second frame may be different from the phase modulation mechanism in the second frame and may be the same as or different from the phase modulation mechanism in the first frame.

[0188] For example only, for reference. Figure 23 In frame 10, the phase of layer position S11 is modulated along the spatial dimension according to a first phase modulation mechanism, alternating between -90° and 90°. The phase of layer position S11 is also modulated along the temporal dimension, resulting in a second phase modulation mechanism corresponding to frame 11 that differs from the first. According to the second phase modulation mechanism, the phase of layer position S11 alternates between 90° and -90° along the spatial dimension in frame 11. In the corresponding PE steps applied in frames 10 and 11, the phase of layer position S11 changes by 180°, i.e., the global phase offset of layer position S11 is 180°. As another example, refer to... Figure 24 The phase of layer position S13 alternates between 180° and 0° along the spatial dimension in frame 12, and alternates between 0° and 180° along the spatial dimension in frame 13. In the corresponding PE steps applied in frames 12 and 13, the phase of layer position S13 changes by 180°, that is, the global phase offset of layer position S13 is 180°.

[0189] In some embodiments, phase modulation at the target layer location can be achieved using various phase modulation techniques described elsewhere in this specification (e.g., steps 602 and 1401 and their related descriptions), such as phase-modulated radio frequency excitation pulses, magnetic field gradients (e.g., phase-modulated gradients along the layer coding direction), compensated magnetic field gradients, etc., or any combination thereof. In some embodiments, phase modulation applied to the target layer location can be used to achieve automated (or self-calibrated) multi-band imaging, i.e., a single-band reference layer image can be extracted from a set of k-space data itself without additional reference scans. Further description of phase modulation applied to the target layer location can be found elsewhere in this specification. See, for example, the description of phase modulation applied to a second layer location as described in step 1401.

[0190] In some embodiments, for each frame, the corresponding set of k-space data may be a set of fully sampled k-space data acquired through full sampling. Alternatively, for each frame, the corresponding set of k-space data may be a set of undersampled k-space data acquired according to the undersampled pattern in the frame. The sampling patterns corresponding to different frames may be the same or different. As an example only, a pseudo-random sampling pattern may be used in at least one of at least two (or more) frames to randomly acquire PE lines in at least one frame. In some embodiments, the undersampled patterns of a pair of adjacent frames may be different and / or interleaved. In some embodiments, after averaging the undersampled k-space data of at least two (or more) frames, one or more specific regions (e.g., the central region of k-space) may be fully sampled (or nearly fully sampled) to improve the accuracy of image reconstruction based on the undersampled k-space data. Further description of the undersampled pattern can be found elsewhere in this specification. For example, see step 1401 and its related description. The scanning process can be further accelerated by using compressed sensing technology to acquire undersampled k-space data instead of fully sampled k-space data.

[0191] In 2102, the processing device 120 (e.g., quantitative measurement module 506) can generate at least two quantitative maps of at least two (or more) layer locations based on at least two sets of k-space data.

[0192] As used herein, a quantitative plot of a layer location may include the value of a quantitative parameter for each physical point at that layer location. Exemplary quantitative plots of an object may include T1 plots, T2 plots, T2* plots, R2 plots, R2* plots, etc., or any combination thereof.

[0193] In some embodiments, at least two target layer images at at least two (or more) layer locations can be used with at least two quantitative images at at least two (or more) layer locations. Figure 1The target layer image is generated. It can be a layer image of a single layer location. In some embodiments, the target layer image of a layer location can reflect the signal strength at each physical point of the layer location corresponding to the saturation magnetic moment. In some embodiments, the target layer image can have a temporal resolution higher than a threshold (e.g., the temporal resolution of a reference layer image as described elsewhere in this specification). In some embodiments, the processing device 120 can generate the image by performing actions such as... Figure 22 The process 2200 generates at least two quantitative maps of the layer location simultaneously based on the set of k-space data.

[0194] This specification provides systems and methods for improving the efficiency of quantitative measurements by incorporating SMS technology. Compared to conventional techniques that perform quantitative measurements on multiple layer locations separately, the provided systems and methods can utilize SMS technology to simultaneously generate quantitative maps of multiple layer locations. Furthermore, in some embodiments, the provided systems and methods can utilize a specially designed phase modulation mechanism to achieve automatically calibrated multi-band imaging, and the target layer image of the layer location can be correlated with the quantitative data of the layer location. Figure 1 In other words, layer separation is achieved through phase modulation without additional scanning to generate reference layer images, which improves scanning and reconstruction efficiency and avoids errors that may occur in additional scanning.

[0195] In some embodiments, phase modulation may be applied along the time dimension to one or more target slice locations at at least two (or more) slice locations. Due to the phase modulation along the time dimension, the differences between MRI signals acquired at the target slice locations in different frames may be amplified, and information from different slice locations may be more easily separated, which can improve the signal-to-noise ratio (SNR) of the generated quantitative map and the target slice image. Furthermore, according to some embodiments of this specification, compressed sensing techniques can be utilized, and at least two sets of undersampled k-space data can be acquired based on one or more specific undersampled patterns in the frame. Using compressed sensing techniques can further accelerate the data acquisition process and shorten scan time.

[0196] Figure 22 This is a flowchart illustrating an exemplary process for generating at least two quantitative maps of at least two(multiple) layer locations, according to some embodiments of this specification. In some embodiments, one or more steps of process 2200 may be performed to achieve, as in combination with... Figure 21 At least a portion of step 2102.

[0197] As described in step 2102, the quantitative chart may include a T1 chart, a T2 chart, a T2* chart, an R2 chart, an R2* chart, or any combination thereof. For illustrative purposes, the generation of the T1 chart at the reference layer location is described below, and is not intended to limit the scope of this specification.

[0198] In 2201, the processing device 120 (e.g., quantitative measurement module 506) can determine one or more reconstruction parameters based on at least two sets of k-space data.

[0199] For example, an MRI scanner may include multiple receiving coils for echo signal detection, and reconstruction parameters may include at least two coil sensitivity maps of the receiving coils. For SMS imaging, reconstruction parameters may include at least two coil sensitivity maps of the receiving coils corresponding to each slice location. In some embodiments, for each slice location, processing device 120 may generate a reference slice image of the slice location based on at least two sets of k-space data. Processing device 120 may also determine at least two coil sensitivity maps corresponding to each slice location based on the reference slice image of the slice location. The coil sensitivity map of each slice location may be specified as part of one or more reconstruction parameters. As described in step 603, the reference slice image of the slice location refers to an image representing the slice location in more than one frame of at least two frames (or more frames). The reference slice image may have a lower temporal resolution than the target slice image to be reconstructed in 2203. In some embodiments, for each slice location, processing device 120 may generate at least two coil images of at least two (or more) receiving coils based on the reference slice image of the slice location, and then generate a coil sensitivity map of the slice location based on the coil images. For example, a combined image of coil images can be generated based on the sum of squares (SOS) algorithm, and the coil sensitivity of a particular receiving coil can be determined by dividing the corresponding coil image by the combined image.

[0200] In some embodiments, the at least two sets of k-space data may be at least two sets of fully sampled k-space data acquired in a frame. The processing device 120 may reconstruct an aliased image corresponding to each frame based on the corresponding set of fully sampled k-space data, and generate a reference layer image based on the aliased image of the frame (e.g., by combining two or more aliased images). Further description of generating a reference layer image based on fully sampled k-space data can be found elsewhere in this specification. For example, see steps 602 and 603 and their related descriptions. In some embodiments, if a set of k-space data consists of at least two sets of undersampled k-space data acquired in a frame, the processing device 120 may perform actions such as... Figure 14 The step 1402 or as described above Figure 15 The process 1500 generates a reference layer image based on the set of undersampled k-space data.

[0201] In 2202, the processing device 120 (e.g., quantitative measurement module 506) can construct an optimization function that includes at least two quantitative maps at at least two layer locations, at least two target layer images at at least two layer locations, one or more reconstruction parameters, and at least two sets of k-space data.

[0202] In some embodiments, an optimization function can be reconstructed based on a signal model that establishes the relationship between waiting time and quantitative parameters of at least two quantitative maps corresponding to at least two(multiple) layer locations. As an example only, for a T1 map, an optimization function can be constructed based on an inversion recovery signal model that establishes the relationship between TI and T1. For illustrative purposes, assuming that the layer locations to be imaged simultaneously include two layer locations (i.e., a first layer location and a second layer location), an exemplary optimization function (12) for T1 imaging is shown below:

[0203]

[0204] Where y represents at least two sets of k-space data acquired in the frame, x1′ represents the target layer image at the first layer position, and T 1_1 The T1 image represents the first layer position, x2′ represents the target layer image at the second layer position, and T... 1_2 The T1 plot represents the position of the second layer, s1 represents the coil sensitivity plot corresponding to the position of the first layer, and s2 represents the coil sensitivity plot corresponding to the position of the second layer. Let represent the inversion recovery signal model, D represent the k-space sampling operator, F represent the Fourier transform operator, p1 represent the phase modulation mechanism applied to the first layer position in the frame, p2 represent the phase modulation mechanism applied to the second layer position in the frame, and λ1 represent the indicator ‖T′x1′‖. 1 The regularization parameter for importance, λ2, indicates the level of importance of ||T′x2′||. 1 The importance regularization parameter, T′, represents the total variation operator of the space.

[0205] In the optimization function (12), x1′, x2′, T 1_1 and T 1_2 There may be unknown factors to be addressed. In some embodiments, the spatial total variation operator T′ can reflect the spatial variation of pixel values ​​(or voxel values) in the image, for example, it can be associated with the difference between the pixel values ​​of adjacent pixels or the voxel values ​​of adjacent voxels in the image. The spatial total variation operator T′ in the optimization function (12) can be used to impose constraints on the spatial variation of pixel values ​​(or voxel values) of the target layer image and make the target layer image smoother. In some embodiments, the target layer image x1' can reflect the signal strength of each physical point at the first layer location corresponding to the saturation magnetic moment, and the target layer image x2' can reflect the signal strength of each physical point at the second layer location corresponding to the saturation magnetic moment. In some embodiments, the inversion recovery signal model It can be expressed in the following forms: Where x represents the target layer image at the layer location, T1 represents the T1 image at the layer location, TI represents the inversion time, and S0 represents the signal strength at the layer location corresponding to the saturation magnetic moment. In some embodiments, in the inversion recovery signal model In this context, S0 can be replaced by x.

[0206] It should be noted that the optimization function (12) provided above is merely an example and is not intended to be restrictive. The optimization function (12) can be modified according to actual needs. For example, one or more coefficients can be omitted or replaced with other similar coefficients, and / or one or more additional coefficients can be added. As an example only, the spatial total variation operator T′ can be replaced by another sparse operator. Alternatively, λ1|T′x1′|1 and λ2|T′x2′|1 can be omitted. Furthermore, if a set of k-space data is fully sampled k-space data, D can be omitted.

[0207] In 2203, the processing device 120 (e.g., the quantitative measurement module 506) can generate at least two quantitative maps at at least two (or more) layer locations by solving an optimization function.

[0208] In some embodiments, at least two (or more) target layer images and at least two (or more) quantitative maps at layer positions can be generated simultaneously by solving an optimization function. For example, the target layer image x1' at the first layer position, the target layer image x2' at the second layer position, and the T1 map T at the first layer position can be solved simultaneously to minimize the optimization function (12). 1_1 T1 diagram of the second layer position 1_2 In some embodiments, after determining the T1 map of the layer location and the target layer image, the processing device 120 can perform processing according to the inversion recovery signal model. Generate a layer image corresponding to any layer location in the TI. For example, this can be achieved by combining the target layer image x1', T1 image T... 1_1 and specific TI input to inverted recovery signal model In this process, a layer image corresponding to the first layer position of a specific TI is generated. As another example, this can be achieved by combining the target layer image x1', T1 image T... 1_1 and the TI input to the inverted recovery signal model corresponding to a specific frame This generates a layer image corresponding to the first layer position of a specific frame.

[0209] According to some embodiments of this specification, optimization functions can be constructed to simultaneously determine quantitative maps and target layer images of multiple layer locations of an object. Utilizing optimization functions can improve the efficiency of quantitative measurements. For example, with conventional T1 mapping techniques, multiple acquisitions with different time intervals (TIs) may be required at a single layer location to obtain multiple images corresponding to multiple TIs, and the T1 map of the layer location can be determined through signal fitting. By using the optimization functions disclosed herein, the raw k-space data corresponding to different TIs (or frames) can be used, thereby avoiding the need for image reconstruction and signal fitting and saving computational resources (e.g., computation time and / or required storage space). Furthermore, the optimization function can combine quantitative maps and target layer images of multiple layer locations, allowing multi-dimensional information to be determined together by solving the optimization function. Additionally, the optimization function can be constructed based on an inversion recovery signal model, which can improve the signal-to-noise ratio of the generated T1 map.

[0210] It should be noted that the above description of processes 2100 and 2200 is for illustrative purposes only and is not intended to limit the scope of this specification. Various changes and modifications can be made by those skilled in the art based on the teachings of this specification. However, these changes and modifications do not depart from the scope of this specification. In some embodiments, processes 2100 and / or 2200 may be performed by one or more additional steps not described and / or by omitting one or more steps discussed above. For example, process 2200 may include an additional step of sending a quantitative map and a target layer image to a terminal device (e.g., a physician's terminal device 140) for display. In some embodiments, two or more steps, such as steps 2201 and 2202, may be integrated into a single step or performed in any order.

[0211] Figure 23 This is a schematic diagram illustrating exemplary pulse sequences according to some embodiments of this specification. It can be used as follows... Figure 23 The pulse sequence shown is used to generate the T1 map and the target layer image for each layer position in layer positions S10 and S11. Figure 23 As shown, in frame 10, IR pulses can be applied to layer positions S10 and S11, and a GRE pulse sequence 2300 can be applied after a wait time TI1. In frame 11, IR pulses can be applied to layer positions S10 and S11, and a GRE pulse sequence 2300 can be applied after a wait time TI2. TI1 can be different from TI2. The GRE pulse sequence 2300 can be applied in frames 10 and 11 with different modulation mechanisms.

[0212] For illustrative purposes, the following description will use the application of the GRE pulse sequence 2300 in frame 10 as an example. In each PE step of frame 10, an excitation RF pulse (e.g., a multi-band RF pulse) with a layer-selective gradient can be applied to simultaneously excite layer positions S10 and S11, and echo signals can be acquired from layer positions S10 and S11. The echo signals acquired in each PE step of frame 10 can be stored as PE lines in a k-space matrix corresponding to frame 10.

[0213] To achieve automated calibration of multi-band imaging, a phase modulation gradient can be applied to layer position S11 during each PE step of frame 10, such that the phase of layer position S11 can alternate between -90° and 90° along the spatial dimension (i.e., the phase encoding direction) in frame 10. Furthermore, the phase of layer position S11 can be modulated along the temporal dimension. For example, as... Figure 23 As shown, for the corresponding PE steps in frames 10 and 11, the phase of layer position S11 can be changed by a global phase offset of 180°.

[0214] In some embodiments, due to the phase modulation applied to layer position S11, the processing device 120 can generate reference layer images of layer positions S10 and S11 based on the echo signals acquired in frames 10 and 11, without requiring additional reference scans of layer positions S10 and S11. The generation of the reference layer images of layer positions S10 and S11 can be similar to... Figure 7 The method of generating reference layer images for layer positions S1 and S2 is described above and will not be repeated here. The reference layer images can also be used for quantitative measurements at layer positions S10 and S11. For example, the processing device 120 can determine a set of coil sensitivity maps corresponding to layer position S10 and a set of coil sensitivity maps corresponding to layer position S11 based on the reference layer images. The processing device 120 can simultaneously generate T1 maps and target layer images for layer positions S10 and S11 by solving an optimization function (12) based on k-space data acquired in the 10th and 11th frames, the coil sensitivity maps corresponding to layer positions S10 and S11, and the phase modulation mechanism for layer positions S10 and S11.

[0215] Figure 24 This is a schematic diagram illustrating exemplary pulse sequences according to some embodiments of this specification. It can be used as follows... Figure 24 The pulse sequence shown is used to generate the T1 map and target layer image for each layer position in layer positions S12 and S13 of the object. Figure 24As shown, in frame 12, IR pulses can be applied to layer positions S12 and S13, and an FSE pulse sequence 2400 can be applied after a waiting time TI3. ​​In frame 13, IR pulses can be applied to layer positions S12 and S13, and an FSE pulse sequence 2400 can be applied after a waiting time TI4. TI3 can be different from TI4. Similar to layer position S11, layer position S13 can be phase-modulated along both the spatial and temporal dimensions. Due to the phase modulation applied to layer position S13, reference layer images of layer positions S12 and S13 can be generated based on the echo signals acquired in frames 12 and 13, and these reference layer images can be further used for quantitative measurements of layer positions S12 and S13.

[0216] It should be noted that the above Figure 23 and Figure 24 The exemplary pulse sequences and their descriptions are provided for illustrative purposes only and are not intended to limit the scope of this specification. Various changes and modifications can be made by those skilled in the art based on the teachings of this specification. However, these changes and modifications do not depart from the scope of this specification. In some embodiments, the phase at a specific layer location in a particular PE step can be modulated to any other value different from that shown in the figures. Furthermore, phase modulation in a particular PE step can be achieved by a separate phase modulation gradient, a phase modulation RF excitation pulse, or a combination thereof. Additionally or alternatively, a compensating magnetic field gradient can be applied in each PE step. Furthermore, the frame count can be equal to any positive number, such as 2, 3, 4, etc. For example, processing device 120 can acquire k-space data corresponding to eight frames, and the TI values ​​of the eight frames can be different.

[0217] Furthermore, this specification uses specific terms to describe embodiments thereof. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that "an embodiment," "one embodiment," or "an alternative embodiment" mentioned twice or more in different places in this specification do not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of this specification can be appropriately combined.

[0218] Similarly, it should be noted that, in order to simplify the description disclosed herein and thus aid in the understanding of one or more embodiments of the invention, the foregoing description of embodiments in this specification may sometimes combine multiple features into a single embodiment, drawing, or description thereof. However, this approach in the specification should not be construed as reflecting an intention that the claimed subject matter requires more features than expressly recited in each claim. Rather, the subject of the invention should possess fewer features than in any single embodiment described above.

[0219] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples by the terms "approximately," "approximately," or "substantially." For example, unless otherwise stated, "approximately," "approximately," or "substantially" can indicate a variation of ±1%, ±5%, ±10%, or ±20% of the value it describes. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters are taken into account for specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of range in some embodiments of this specification are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

[0220] Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments described herein. Other variations may also fall within the scope of this specification. Therefore, alternative configurations of the embodiments described herein are intended to be illustrative rather than limiting, and are considered consistent with the teachings of this specification. Accordingly, the embodiments described herein are not limited to those explicitly introduced and described herein.

Claims

1. A magnetic resonance imaging system, comprising: The acquisition module is used to acquire at least two sets of k-space data corresponding to at least two frames, wherein, in one of the at least two frames, a magnetic resonance imaging scanner is used to simultaneously acquire each set of k-space data from at least two layer locations of the object, and there is a waiting time after a preparation pulse is applied in the frame; the preparation pulse is applied to the at least two layer locations of the object to determine one or more quantitative parameters of the at least two layer locations; the waiting time is the time interval between the preparation pulse and the first excitation pulse in a pulse sequence for performing the PE step during the frame; and The quantitative measurement module is used to generate at least two quantitative maps of at least two layer locations based on the at least two sets of k-space data, wherein In the at least two frames, phase modulation is applied to at least one target layer position among the at least two layer positions to perform interlayer separation; At least two target layer images at the at least two layer locations are generated together with at least two quantitative maps at the at least two layer locations.

2. The system according to claim 1, characterized in that, The one or more quantitative parameters include at least one or a combination of T1, T2, transverse relaxation attenuation, signal attenuation rate, transverse relaxation rate, etc.

3. The system according to claim 1, characterized in that, The waiting time is related to the location of the layer to be imaged.

4. The system according to claim 1, characterized in that, The generation of at least two quantitative maps for at least two layer locations based on the at least two sets of k-space data includes: One or more reconstruction parameters are determined based on the at least two sets of k-space data; Construct an optimization function, the optimization function comprising at least two quantitative maps at the at least two layer locations, at least two target layer images at the at least two layer locations, one or more reconstruction parameters, and at least two sets of k-space data; and By solving the optimization function, at least two quantitative maps and at least two target layer images are generated for the at least two layer locations.

5. The system according to claim 4, characterized in that, The optimization function is constructed based on a signal model, which establishes the relationship between the waiting time and the quantitative parameters of at least two quantitative plots corresponding to the at least two layer positions.

6. The system according to claim 4, characterized in that, Determining one or more reconstruction parameters based on the at least two sets of k-space data includes: For each of the at least two layer locations, a reference layer image for that layer location is generated based on the at least two sets of k-space data; and Based on the reference layer images at the at least two layer locations, at least two coil sensitivity maps corresponding to each of the at least two layer locations are used as part of the one or more reconstruction parameters.

7. The system according to claim 1, characterized in that, For each of the at least two frames, the corresponding set of k-space data is a set of undersampled k-space data collected according to the intra-frame undersampling mode.

8. The system according to claim 7, characterized in that, The undersampling patterns of a pair of adjacent frames in at least two frames are interleaved.

9. A non-transitory computer-readable medium comprising a set of instructions for image stitching, characterized in that, When executed by at least one processor, the set of instructions instructs the at least one processor to implement a method comprising: Acquire at least two sets of k-space data corresponding to at least two frames, wherein, in one of the at least two frames, a magnetic resonance imaging scanner is used to simultaneously acquire each set of k-space data from at least two layer locations of the object, and a waiting time follows the application of a preparation pulse in the frame; the preparation pulse is applied to the at least two layer locations of the object to determine one or more quantitative parameters of the at least two layer locations; the waiting time is the time interval between the preparation pulse and the first excitation pulse in a pulse sequence for performing the PE step during the frame; and At least two quantitative maps are generated based on the at least two sets of k-space data for the at least two layer locations, wherein In the at least two frames, phase modulation is applied to at least one target layer position among the at least two layer positions to perform interlayer separation; At least two target layer images at the at least two layer locations are generated together with at least two quantitative maps at the at least two layer locations.

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