Medical scanning data processing method and system

Abstract

The embodiment of the invention provides a medical scanning data processing method and system, and the method comprises the steps: obtaining a plurality of groups of echo signals which correspond to a plurality of channel coils; generating a field distribution diagram based on the multiple groups of echo signals, and determining baseline phase diagrams of the multiple channel coils through the field distribution diagram; performing phase correction on the multiple groups of echo signals based on the baseline phase diagram to obtain multiple groups of corrected signals; and performing multi-channel merging based on the multiple groups of corrected signals, and determining a merged image.

Description

Technical Field

[0001] This specification relates to the technical field of magnetic resonance imaging, and particularly relates to a method and system for processing medical scan data. Background Art

[0002] With the development of magnetic resonance imaging technology, multi-channel phased array coils are widely used in magnetic resonance imaging scans. Each coil unit of each array coil has an independent signal receiving ability, that is, it corresponds to an independent signal channel respectively, and the signals of each channel correspond to the signals generated by the excitation of the same object. The signals of multiple channels are processed and combined to obtain a final image (amplitude map or phase map). However, the current channel combination method for phase has problems such as being sensitive to noise and artifacts, and the foregoing problems may have an adverse impact on the quality of the combined image.

[0003] Therefore, it is desirable to propose a method and system for processing medical scan data to obtain high-quality medical images. Summary of the Invention

[0004] One or more embodiments of this specification provide a method for processing medical scan data. The method for processing medical scan data includes: acquiring multiple sets of echo signals, where the multiple sets of echo signals correspond to multiple channel coils; generating a field distribution map based on the multiple sets of echo signals, and determining a baseline phase map of the multiple channel coils through the field distribution map; performing phase correction on the multiple sets of echo signals based on the baseline phase map to obtain multiple sets of corrected signals; and performing multi-channel combination on the multiple sets of corrected signals to determine a combined image.

[0005] In some embodiments, the echo signals are complex signals.

[0006] In some embodiments, the acquisition method of each set of echo signals in the multiple sets of echo signals includes: acquiring echo signals of multiple echoes with different echo times and the same or different echo intervals.

[0007] In some embodiments, the echo signals include at least two dimensions of echo time and channel coil, and the generating a field distribution map based on the multiple sets of echo signals includes: calculating the field distribution map by a complex method of multi-echo imaging using multiple sets of complex echo signals acquired by the multiple channel coils at multiple echo times; or extracting the phases of the corresponding multiple sets of echo signals from the multiple sets of complex echo signals acquired by the multiple channel coils at multiple echo times, and calculating the field distribution map by a fitting method.

[0008] In some embodiments, determining the baseline phase diagram of the plurality of channel coils based on the field distribution diagram includes: obtaining multiple sets of candidate complex echo signals, where the multiple sets of candidate complex echo signals correspond to the plurality of channel coils; and determining the baseline phase diagram based on the multiple sets of candidate complex echo signals through complex number calculations.

[0009] In some embodiments, each set of candidate complex echo signals in the multiple sets of candidate complex echo signals includes at least one candidate complex echo signal, and the method further includes: determining the baseline phase diagram of the corresponding channel based on the phase information of the at least one candidate complex echo signal.

[0010] In some embodiments, performing multi-channel merging based on the multiple sets of corrected signals to determine the merged image includes: generating the merged image based on the multiple sets of corrected signals through a preset merging method, where the preset merging method includes direct complex number addition merging, complex number weighted merging, and correlation calculation methods; and determining the target image based on the merged image.

[0011] One or more embodiments of this specification provide a medical scan data processing system. The system includes an acquisition module, a determination module, a correction module, and a generation module; the acquisition module is configured to acquire multiple sets of echo signals, where the multiple sets of echo signals correspond to the plurality of channel coils; the determination module is configured to generate a field distribution diagram based on the multiple sets of echo signals and determine the baseline phase diagram of the plurality of channel coils through the field distribution diagram; the correction module is configured to perform phase correction on the multiple sets of echo signals based on the baseline phase diagram to obtain multiple sets of corrected signals; and the generation module is configured to perform multi-channel merging based on the multiple sets of corrected signals to determine the merged image.

[0012] One or more embodiments of this specification provide a medical scan data processing device, where the device includes at least one processor and at least one memory; the at least one memory is used to store computer instructions; and the at least one processor is used to execute at least part of the computer instructions to implement the medical scan data processing method as described above.

[0013] One or more embodiments of this specification provide a computer-readable storage medium, where the storage medium stores computer instructions, and when a computer reads the computer instructions in the storage medium, the computer executes the medical scan data processing method as described above. Description of the Drawings

[0014] This specification will be further described by way of exemplary embodiments, and these exemplary embodiments will be described in detail through the drawings. These embodiments are not restrictive, and in these embodiments, the same numbers represent the same structures, where:

[0015] Figure 1 is a schematic diagram of the application scenario of a medical scan data processing system shown in some embodiments of this specification;

[0016] Figure 2 is an exemplary block diagram of a medical scan data processing system shown in some embodiments of this specification;

[0017] Figure 3 is an exemplary flowchart of a medical scan data processing method shown in some embodiments of this specification;

[0018] Figure 4 is an exemplary flowchart of a method for determining a baseline phase map shown in some embodiments of this specification;

[0019] Figure 5 is an exemplary schematic diagram of the original phase map, baseline phase map, and corrected phase map of each channel shown in some embodiments of this specification;

[0020] Figure 6 is an exemplary schematic diagram of the phase map of each channel and the merged phase map shown in some embodiments of this specification. Detailed implementation manners

[0021] To more clearly illustrate the technical solutions of the embodiments of this specification, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some examples or embodiments of this specification. For those of ordinary skill in the art, without creative efforts, this specification can also be applied to other similar scenarios based on these drawings. Unless obvious from the language context or otherwise stated, the same reference numerals in the figures represent the same structure or operation.

[0022] It should be understood that the "system", "device", "unit" and / or "module" used herein is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the said words can be replaced by other expressions.

[0023] As shown in this specification and the claims, unless the context clearly indicates an exception, words such as "a", "an", "one" and / or "the" are not specifically singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0024] In this specification, flowcharts are used to illustrate the operations performed by the system according to the embodiments of this specification. It should be understood that the preceding or subsequent operations are not necessarily executed precisely in sequence. On the contrary, the steps can be processed in reverse order or simultaneously. Also, other operations can be added to these processes, or one or several operations can be removed from these processes.

[0025] Figure 1 FIG. 1 is a schematic diagram of an application scenario of a medical scan data processing system according to some embodiments of this specification. As Figure 1 shown, the application scenario 100 of the medical scan data processing system (hereinafter referred to as the application scenario 100) may include a magnetic resonance scanning device 110, a network 120, one or more terminals 130, a processing device 140, and a storage device 150.

[0026] The components in the application scenario 100 can be connected in various ways. By way of example only, as Figure 1 shown, the magnetic resonance scanning device 110 can be connected to the processing device 140 via the network 120. As another example, the magnetic resonance scanning device 110 can be directly connected to the processing device 140 (as shown by the bidirectional arrow in the dashed line connecting the magnetic resonance scanning device 110 and the processing device 140). As yet another example, the storage device 150 can be directly or via the network 120 connected to the processing device 140. As a further example, the terminal 130 can be directly connected to the processing device 140 (as shown by the bidirectional arrow in the dashed line connecting the terminal 130 and the processing device 140) or connected via the network 120.

[0027] The magnetic resonance scanning device 110 can scan an object or a part thereof located within its detection area and generate a magnetic resonance signal related to the object or the part thereof. In this specification, the terms "object" and "body" can be used interchangeably. By way of example only, the object can include a patient, an artificial object, etc. For example, the object can include a specific part of a patient, such as an organ, a tissue, etc. or any combination thereof. In some embodiments, the magnetic resonance scanning device 110 can be a near-bore scanner or an open-bore scanner, etc.

[0028] The network 120 can include any suitable network that can facilitate the exchange of information and / or data in the application scenario 100. In some embodiments, one or more components of the application scenario 100 (e.g., the magnetic resonance scanning device 110, the terminal 130, the processing device 140, or the storage device 150) can transmit information and / or data to one or more other components of the application scenario 100 via the network 120. For example, the processing device 140 can obtain a magnetic resonance signal from the magnetic resonance scanning device 110 via the network 120.

[0029] In some embodiments, network 120 may be a wired network, a wireless network, or the like, or any combination thereof. In some embodiments, network 120 may include one or more network access points. For example, network 120 may include wired and / or wireless network access points, such as base stations and / or Internet exchange points, through which one or more components of application scenario 100 may be connected to network 120 to exchange data and / or information.

[0030] Terminal 130 is one or more terminals used by a user. In some embodiments, terminal 130 includes mobile device 131, tablet computer 132, laptop computer 133, etc., or any combination thereof. In some embodiments, terminal 130 may be connected to and operate magnetic resonance scanning device 110 and / or processing device 140. In some embodiments, terminal 130 may receive information and / or instructions input by a user and send the received information and / or instructions to magnetic resonance scanning device 110 or processing device 140 via network 120. In some embodiments, terminal 130 may receive data and / or information from processing device 140. In some embodiments, terminal 130 may be a part of processing device 140. In some embodiments, terminal 130 may be omitted. The above examples are only used to illustrate the wide range of terminal 130 devices rather than to limit its scope.

[0031] Processing device 140 may process data and / or information obtained from magnetic resonance scanning device 110, terminal 130, and / or storage device 150. For example, processing device 140 may acquire multiple sets of echo signals acquired by magnetic resonance scanning device 110. Each set of echo signals in the multiple sets of echo signals may be acquired from a channel corresponding to a coil unit of an array coil of magnetic resonance scanning device 110. For the multiple sets of echo signals, processing device 140 may calculate a field distribution map using a complex method, a fitting method, etc. of multi-echo imaging. Processing device 140 may also perform filtering processing on the field distribution map and determine a baseline phase map based on the filtered field distribution map. Processing device 140 may also correct the multiple sets of echo signals through the baseline phase map to obtain corrected signals corresponding to each channel coil. Processing device 140 may also perform multi-channel merging on the multiple sets of corrected signals to obtain a merged image. Processing device 140 may also extract the merged image to obtain a target image. In some embodiments, processing device 140 may also send the target image to terminal 130 for display on one or more display devices in terminal 130 and / or for storage on a storage device.

[0032] In some embodiments, the processing device 140 may be a single server or a server group. The server group may be centralized or distributed. In some embodiments, the processing device 140 may be local or remote. In some embodiments, the processing device 140 may be implemented on a cloud platform. In some embodiments, the processing device 140 may be implemented on a computing device having one or more components of the medical scan data processing system 200 shown in this specification Figure 2 and described in this specification.

[0033] The storage device 150 may store data and / or instructions. In some embodiments, the storage device 150 may store data obtained from the magnetic resonance scanning device 110, the terminal 130, and / or the processing device 140. For example, the storage device 150 may store multiple sets of echo signals obtained from the magnetic resonance scanning device 110. In some embodiments, the storage device 150 may store data and / or instructions. For example, the storage device 150 may store instructions for the processing device 140 to execute the methods described in some embodiments of this specification. In some embodiments, the storage device 150 includes a mass storage device, a removable storage device, a volatile read-write memory, a read-only memory (ROM), etc., or any combination thereof. In some embodiments, the storage device 150 may be implemented on a cloud platform.

[0034] It should be noted that the above description of the application scenario 100 of the medical scan data processing system is for illustrative purposes only and is not intended to limit the scope of this application. Various variations and modifications can be made by those of ordinary skill in the art according to this application. However, these changes and modifications do not depart from the scope of this application. For example, the application scenario 100 of the medical scan data processing system may further include a display device for outputting the restored first imaging data, the finally generated magnetic resonance image, etc. Also, for example, the magnetic resonance scanning device 110, the processing device 140, and the terminal 130 may share a storage device 150 or may each have their own storage device.

[0035] Figure 2 is an exemplary module diagram of a medical scan data processing system according to some embodiments of this specification.

[0036] As Figure 2 shown, the medical scan data processing system 200 (abbreviated as system 200) may include an acquisition module 210, a determination module 220, a correction module 230, and a generation module 240. In some embodiments, one or more modules in the system 200 may be interconnected, and the connection may be wireless or wired. At least a part of the system 200 may be implemented on the terminal 130 or the processing device 140 as Figure 1 shown.

[0037] In some embodiments, the acquisition module 210 can be used to acquire multiple sets of echo signals, and the multiple sets of echo signals correspond to multiple channel coils.

[0038] In some embodiments, the determination module 220 can be used to generate a field distribution map based on the multiple sets of echo signals, and determine the baseline phase map of the multiple channel coils through the field distribution map.

[0039] In some embodiments, the correction module 230 can be used to perform phase correction on the multiple sets of echo signals based on the baseline phase map to obtain multiple sets of corrected signals.

[0040] In some embodiments, the generation module 240 can perform multi-channel merging based on the multiple sets of corrected signals to determine the merged image.

[0041] For more descriptions of the acquisition module 210, the determination module 220, the correction module 230, and the generation module 240, reference can be made to Figure 3 and its related descriptions.

[0042] It should be noted that the above descriptions of the medical scan data processing system 200 and its modules are only for convenience of description, and do not limit this specification to the scope of the examples given. It can be understood that for those skilled in the art, after understanding the principle of the system, they may, without departing from this principle, make any combination of the various modules, or form a subsystem and connect it with other modules. In some embodiments, Figure 2 the acquisition module 210, the determination module 220, the correction module 230, and the generation module 240 disclosed in

[0043] Figure 3 is an exemplary flowchart of a medical scan data processing method according to some embodiments of this specification. In some embodiments, the process 300 can be executed by Figure 2 the system 200 shown, or can be implemented in Figure 1 the application scenario 100 shown. As Figure 3 shown, the process 300 includes the following steps.

[0044] Step 310, acquire multiple sets of echo signals.

[0045] An echo signal refers to the magnetic resonance signal corresponding to the echo released by an object after being excited by a radio frequency pulse. In some embodiments, the acquisition module 210 may acquire the echo signal through a channel coil. Exemplarily, a radio frequency pulse is applied to excite the nuclear spins of an object. When the excited nuclear spins re-enter the static magnetic field, they begin to release energy, forming an echo signal. The acquisition module 210 may capture the aforementioned echo signal through a channel coil (coil unit).

[0046] In some embodiments, multiple sets of echo signals respectively correspond to multiple channel coils. Each set of echo signals may be acquired by one of the multiple channel coils (coil units). Among them, different channel coils among the multiple channel coils refer to coil units placed at different spatial positions.

[0047] In some embodiments, the acquisition module 210 may use various methods to acquire the echo signal through the channel coil. For example, the acquisition module 210 may use methods such as a unipolar readout gradient or a bipolar readout gradient to acquire the echo signal through the channel coil. Using different methods to acquire the echo signal has a certain impact on the expression of the following formula (2). For more details, see Figure 3 the following description.

[0048] In some embodiments, each set of echo signals includes multiple echo signals. By applying a radio frequency pulse sequence to excite an object and through the channel coil corresponding to this set of echo signals, multiple echo signals are further acquired. A radio frequency pulse sequence refers to multiple radio frequency pulses with a time sequence. The relevant parameters corresponding to the multiple radio frequency pulses may be different. Each echo signal corresponds to a specific radio frequency pulse. One radio frequency pulse sequence corresponds to multiple echo signals. The aforementioned multiple echo signals appear sequentially in time, and each echo signal contains different information about tissue characteristics.

[0049] In some embodiments, the echo signal is a complex signal.

[0050] A complex signal is a representation form of a magnetic resonance signal. The echo signal can be represented in a complex form. A complex signal may contain information such as the amplitude (magnitude) information and phase information of the magnetic resonance signal. In some embodiments, the complex signal may be represented by a complex image signal. The complex image signal can reflect the complete signal state of a specific pixel or voxel in a magnetic resonance image at a certain specific time point. In magnetic resonance imaging, the amplitude information is usually related to the brightness or intensity of the magnetic resonance image. The phase information can be used to generate a phase image, and the phase information is related to the spatial position of the pixel points in the magnetic resonance image.

[0051] In some embodiments, the acquisition module 210 may acquire the echo signals collected by multiple channel coils, analyze and process them to obtain the amplitude information and phase information of the echo signals, use the amplitude information as the real part and the phase information as the imaginary part to obtain a magnetic resonance signal in complex form, that is, a complex signal.

[0052] In some embodiments of this specification, the echo signal is a complex signal. The complex signal includes both amplitude information and phase information, which can better reflect the internal structure and physiological state of the human body, and helps to obtain a more accurate phase image with a better signal-to-noise ratio subsequently. In addition, calculating based on the complex image signal reduces the amount of calculation and improves the calculation efficiency compared with calculating based on the phase image.

[0053] In some embodiments, the acquisition module 210 may acquire the echo signals of multiple echoes with different echo times and the same or different echo intervals.

[0054] The echo time refers to the time interval between the excitation of hydrogen nuclei by a radio frequency pulse and the reception of the echo signal.

[0055] In some embodiments, the radio frequency pulse sequence may include multiple types. For example, a spin echo sequence, a gradient echo sequence, etc. The echo times corresponding to different radio frequency pulse sequences may be different. For example, in a spin echo sequence, first, a 90° radio frequency pulse is applied to excite the nuclear spin, making the hydrogen nuclei enter a temporary excited state. As time passes, the hydrogen nuclei enter a free precession state, and then a 180° phase rephasing pulse (also called an inversion pulse) is applied to re-aggregate the phases of the nuclear spins, and then a macroscopic magnetization vector is generated in a certain direction. Subsequently, when these hydrogen nuclei of the spins re-enter the static magnetic field, they will release energy to form an echo signal, and the acquisition module 210 may acquire this echo signal through the channel coil. The time period between the time point when the inversion pulse is applied and the time point when the echo signal is received is the echo time corresponding to the spin echo sequence (such as echo time 1). In a gradient echo sequence, a gradient magnetic field is automatically applied after the radio frequency pulse is applied to cause the hydrogen nuclei to shift in position in space. When the hydrogen nuclei return to the equilibrium position, they will release energy to form an echo signal, and the acquisition module 210 may acquire this echo signal through the channel coil. The time period between the time point when the gradient magnetic field is applied and the time point when the echo signal is received is the echo time corresponding to the gradient echo sequence (such as echo time 2). Since the excitation methods of different radio frequency pulse sequences are different, the magnitudes of the corresponding echo time 1 and echo time 2 may be different. In some embodiments, the processing device may change the relevant parameters of each radio frequency pulse in the radio frequency pulse sequence to acquire the echo signals of multiple echoes with different echo times.

[0056] The echo interval refers to the time interval between two consecutive echo signals. In some embodiments, the echo interval can be represented by the time interval between the time points corresponding to two consecutive radio frequency pulses. For example, in a spin echo sequence, the echo interval can refer to the time interval between two consecutive 180° phase rephasing pulses. In a gradient echo sequence, the echo interval can refer to the time interval between two consecutive automatically applied gradient magnetic fields. The length of the echo interval is related to the scanning speed and the image quality obtained in subsequent steps. If the echo interval is too short, it may cause signal overlap and affect the image quality; if the echo interval is too long, it may cause the scanning speed to slow down and increase the scanning time. In some embodiments, the processing device can set the length of the echo interval, the same or different, based on actual needs.

[0057] In some embodiments, the processing device can set the radio frequency pulse sequence based on actual needs, and the radio frequency pulse sequence can correspond to different echo times and the same or different echo intervals.

[0058] In some embodiments of this specification, the acquisition module 210 can acquire the echo signals of multiple echoes with different echo times and the same or different echo intervals. Different echo times help to acquire the magnetic resonance information of the object at different time points, can better reflect the response of the object at different time points, and further can obtain the physiological state and changes of the object at different time points, thereby improving the quality of the subsequent phase image and making it more accurately reflect the true state of the tissue. In addition, the same echo interval can ensure the stability and accuracy of the image quality. Different echo intervals can ensure the diversity of the acquired image phase information.

[0059] In some embodiments, the echo signal includes at least two signal dimensions: the echo time and the signal channel. Among them, the signal channel refers to the channel coil that collects the echo signal. For example, for the m-th channel coil, the echo signal corresponding to the n-th echo can be represented as S m,n . Where m is an integer, n is an integer, and the value of m can be greater than or equal to 2, and the value of n can be greater than or equal to 2. S m,n is positively correlated with the amplitude sensitivity intensity of the m-th channel coil, the inhomogeneity of the magnetic field deviating from the central field strength, the echo time of the n-th echo, and the phase sensitivity value of the m-th channel coil, etc. The above relationship can be represented by formula (1):

[0060]

[0061] Where M m is the amplitude sensitivity intensity of the m-th channel coil (such as signal amplitude, intensity, etc.); e i is the representation form of a complex number; γ is the gyromagnetic ratio; ΔB0 is a value characterizing the inhomogeneity of the magnetic field deviating from the central field strength and the distribution of the field; TEn is the echo time of the nth echo; is a value representing the phase sensitivity of the mth channel coil, which is unknown and can be obtained through calculation later.

[0062] In some embodiments, each group of echo signals corresponding to the channel coils may contain information unique to the corresponding channel coil. For example, assuming there are m channel coils, the m groups of echo signals of the m channel coils can be expressed as S = {S1, S2,..., S m}, where S represents the set of multiple groups of echo signals of multiple channels, S1 represents the first group of echo signals corresponding to the first channel coil, S2 represents the second group of echo signals corresponding to the second channel coil,..., S m represents the mth group of echo signals corresponding to the mth channel coil. Since the spatial sensitivity distribution, acquisition, noise, and other parameters of multiple channel coils are different and vary greatly, the information contained in the echo signals collected by each channel coil will be different. For example, the coil placement position of the first channel coil is different from that of the second channel coil, and the echo signals of the target object that it can collect are also different. Exemplarily, the first channel coil can collect some information that the second channel coil cannot collect, and this information can be understood as the information unique to the channel coil.

[0063] In some embodiments, the magnetic resonance signals corresponding to different echoes may contain information unique to the echoes. For example, the longer the echo time, the greater the magnetic field accumulation effect of the magnetic resonance signal corresponding to the echo, and the greater the corresponding phase change. Exemplarily, assuming the mth channel, the magnetic resonance signals of its corresponding n echoes can be expressed as S m = {S m,1 , S m,2 ,..., S m,n}, where S m,1 represents the first echo signal of the mth channel coil, S m,2 represents the second echo signal of the mth channel coil,..., S m,n represents the nth echo signal of the mth channel coil. The echo times of multiple echoes are different, so the information contained in the different echo signals collected by each channel will be different.

[0064] Step 320, generate a field distribution map based on multiple groups of echo signals, and determine the baseline phase maps of multiple channel coils through the field distribution map.

[0065] The field distribution refers to the spatial distribution of the magnetic field. The field distribution map can reflect the magnetic field intensity and / or phase change at each position in the imaging region. For example, the field distribution map can characterize the phase change caused by the field distribution within the echo interval time (ΔTE) between two echoes.

[0066] In some embodiments, the determining module 220 may generate a field distribution map in a variety of ways based on multiple sets of echo signals. For example, the determining module 220 may utilize the aforementioned multiple sets of echo signals, analyze the multiple sets of echo signals, obtain the signal amplitude and phase information collected at each pixel or voxel, calculate the magnetic field strength or phase change at each pixel or voxel, and thereby generate a field distribution map.

[0067] In some embodiments, the echo signals include at least two dimensions of echo time and channel coil, and for more details, reference may be made to the relevant description of step 310. In some embodiments, the determining module 220 may calculate a field distribution map by a complex method of multi-echo imaging using multiple sets of complex echo signals collected by multiple channel coils at multiple echo times. In some embodiments, the determining module 220 may extract the phases of the corresponding multiple sets of echo signals from multiple sets of complex echo signals collected by multiple channel coils at multiple echo times, and calculate a field distribution map by a fitting method.

[0068] A complex echo signal refers to an echo signal represented in a complex form.

[0069] The complex method of multi-echo imaging is a method for estimating the magnetic field strength at each pixel point. For example, the Multiple Dimension Integration (MDI) method, etc. The fitting method is a method for fitting the phases of multiple sets of echo signals.

[0070] In some embodiments, the determining module 220 may utilize the echo time and channel coil information of multiple sets of echo signals, associate the echo time and channel coil information of each complex echo signal with the corresponding pixel point, and use the complex method of multi-echo imaging to calculate the magnetic field strength distribution at each pixel point, and further determine the field distribution map.

[0071] Exemplarily, the complex method of multi-echo imaging or the fitting method may be expressed as formula (2):

[0072]

[0073] where, Θ represents the field distribution map, and the field distribution map can be represented in a complex form of the magnetic field strength and / or phase value at each pixel or voxel; N e is the total number of echoes, and calculations are performed once between every two echoes, and thus represented as N e -1; N c is the total number of channels, and there is no need to calculate pairwise. On the premise that n is N e -1, it needs to be represented as n + 1; S m,n * is Sm,n its conjugate complex number; ΔTE is the echo interval.

[0074] In some embodiments, the determination module 220 may calculate the complex form of the magnetic field intensity or phase value of each pixel or voxel through formula (2). The complex form of the magnetic field intensity or phase value is positively correlated with The determination module 220 then calculates ΔB0. When ΔB0 is known, the determination module 220 may calculate

[0075] In some embodiments, the multiple sets of complex echo signals corresponding to the above formula (2) are echo signals collected using a unipolar readout gradient, and ΔTE is the echo time difference between adjacent echoes. When the acquisition module 210 collects complex echo signals using a bipolar readout gradient, ΔTE in formula (2) is the echo time difference between adjacent odd echoes (or even echoes), and S in formula (2) m,n+1 needs to be modified to S m,n+2 .

[0076] In some embodiments of the present description, the echo signal includes at least two dimensions of echo time and channel coil. The echo time can provide information about tissue magnetization, while the channel coil can provide information about magnetic field intensity and coil position. Using multiple sets of complex echo signals collected by multiple channel coils at multiple echo times, through the complex method of multi-echo imaging or extracting the phases of the corresponding multiple sets of echo signals, and through the fitting method, a field distribution map containing richer information such as magnetic field intensity distribution can be obtained, which helps to improve the calculation efficiency and accuracy of subsequent steps, and at the same time helps doctors better understand the magnetic susceptibility and magnetic permeability of different objects.

[0077] The baseline phase refers to the phase influence that the inherent properties of the channel coil may cause to the magnetic resonance signal. For example, due to differences in the position, size, and circuit design of the channel coil, the phase influence on the magnetic resonance signal received by the channel coil is different.

[0078] The baseline phase map can reflect the phase distribution of one or more pixel points corresponding to the channel coil before the start of the scan. For example, when there is no echo or the echo time is 0, the baseline phase map can reflect the initial phase state of each pixel point.

[0079] In some embodiments, the determining module 220 may process the field distribution map to obtain a baseline phase map. For example, the determining module 220 may extract phase information based on the field distribution map including magnetic field strength or phase distribution information. The phase value of each pixel of the field distribution map represents the magnetic field strength and phase information at that position. The determining module 220 may use the phase value of each pixel as the abscissa and the position coordinate of the pixel as the ordinate to draw an image, thereby obtaining the baseline phase map of each channel. In some embodiments, the determining module 220 may also represent the magnitude of the phase values of different pixels by color or gray level, which helps to more intuitively display the magnetic field strength and distribution. For more details, please refer to Figure 5 and / or Figure 6 the relevant description of

[0080] In some embodiments, the determining module 220 may also perform smoothing filtering on the field distribution map in the complex domain to obtain a filtered field distribution map, and obtain the baseline phase map of each channel coil based on the filtered field distribution map. Among them, the smoothing filtering process may include any low-pass filtering method that can remove high spatial frequency components and retain low spatial frequency components. This specification does not limit this.

[0081] In some embodiments, since the echo signal with an echo time of 0 is an ideal state and is difficult to measure in actual detection, the determining module 220 may determine the baseline phase signal of each channel through a preset baseline algorithm. Based on the baseline phase signal, the phase information of the corresponding pixel can be obtained, and then the baseline phase map of each channel can be generated. An exemplary preset baseline algorithm is represented by formula (3):

[0082]

[0083] where S m,0 is the baseline phase signal of the m-th channel, Θ smooth is the complex form of the magnetic field strength or phase value of the pixel or voxel in the filtered field distribution map, is the conjugate complex number of Θ smooth

[0084] In some embodiments, the determining module 220 may determine the baseline phase maps of multiple channel coils based on multiple groups of candidate complex echo signals. For more details, please refer to Figure 4 and its relevant description.

[0085] Step 330: Perform phase correction on multiple groups of echo signals based on the baseline phase map to obtain multiple groups of corrected signals.

[0086] ​The corrected signal refers to the echo signal after baseline phase correction. Each set of corrected signals is the corrected signal of different echo signals in the same group corresponding to the same channel coil. Multiple sets of corrected signals respectively correspond to the corrected signals of a group of different echo signals corresponding to multiple channel coils respectively.

[0087] In some embodiments, the correction module 230 can remove the baseline phase signal in each set of echo signals to obtain the corrected signal corresponding to each set of echo signals. For example, the correction module 230 can remove S m,0 from a set of echo signals corresponding to the m-th channel by complex division to obtain the echo signal after baseline phase correction, that is, the corrected signal corresponding to the m-th channel coil. Exemplarily, the correction module 230 can obtain the corrected signal through the following formula (4):

[0088]

[0089] where S′ m,n is the corrected signal, is the conjugate complex number corresponding to the baseline phase signal.

[0090] In some embodiments, the correction module 230 can obtain the corrected signal corresponding to each channel coil in multiple channel coils through formula (4).

[0091] Step 340, perform multi-channel merging based on multiple sets of corrected signals to determine the merged image.

[0092] The merged image refers to the image obtained by merging the magnetic resonance signals of multiple channels.

[0093] Multi-channel merging refers to the process of merging the magnetic resonance signals (e.g., corrected signals) of multiple channel coils. Each multi-channel merging is to merge the magnetic resonance signals of multiple channel coils of the same echo signal. For example, the generation module 240 can reconstruct the corrected signals of the same echo signal corresponding to each of the multiple channel coils to obtain the channel images corresponding to each of the multiple channels, and then merge the multiple channel images into one image, and the obtained one image is a merged image. Another example is that the generation module 240 can also perform merging processing on multiple sets of corrected signals S′ m,n in the channel dimension to obtain the merged data S n,comb , and then reconstruct to obtain the merged image. The generation module 240 can obtain the merged images corresponding to different echo signals respectively through the above method.

[0094] In some embodiments, the generating module 240 may generate a merged image based on the corrected signal through a preset merging method. In some embodiments, the generating module 240 may determine a target image based on the merged image.

[0095] The preset merging method refers to a preset method for merging signals. In some embodiments, the preset merging method includes at least one of direct complex addition merging, complex weighting merging, and correlation calculation method, etc. The following are embodiments in which after obtaining multiple sets of corrected signals in step 330, the generating module 240 generates a merged image through different preset merging methods (Embodiment 1, Embodiment 2, and Embodiment 3).

[0096] Embodiment 1

[0097] In some embodiments, the generating module 240 may directly perform complex addition merging on the corrected signals based on direct complex addition merging (such as according to the following formula (5)) to obtain merged data S n,comb :

[0098]

[0099] Furthermore, the generating module 240 may reconstruct to obtain the merged image.

[0100] Embodiment 2

[0101] In some embodiments, the generating module 240 may perform complex weighting merging on the corrected signals based on complex weighting merging (such as according to the following formula (6)) to obtain merged data S n,comb :

[0102]

[0103] Wherein, W m is the weight coefficient of the m-th channel coil corresponding to the corrected signal S′ m,n The magnitudes of the weight coefficients of different channel coils can be preset according to actual requirements.

[0104] Furthermore, the generating module 240 may reconstruct to obtain the merged image.

[0105] Embodiment 3

[0106] In some embodiments, the generating module 240 may determine the merged image through a correlation calculation method. The generating module 240 may determine reference data, extract the phase offset of the corrected signal of each channel coil relative to the reference data through the cross-correlation method, and perform phase correction based on the phase offset, and merge the phase-corrected multiple sets of corrected signals to obtain merged data S n,comb, and then the merged image is reconstructed. Among them, the cross-correlation method refers to an algorithm that can calculate the cross-correlation coefficient between two sets of data. The reference data can include signal data of any one channel, the result obtained by merging partial channels, and data obtained through virtual coils, etc. The phase offset refers to the phase change of the corrected signal of each channel relative to the reference data. The generation module 240 can use the cross-correlation method to determine the cross-correlation coefficient between the corrected signal and the reference data. The generation module 240 can determine the phase offset between the corrected signal and the reference data based on the cross-correlation coefficient. In some embodiments, the element value of each element of the corrected signal and the reference data is represented by a complex number including phase information and amplitude information. In order to use the cross-correlation method to determine the cross-correlation coefficient between the corrected signal and the reference data, the generation module 240 can determine the first average value of the element values of the corrected signal and the second average value of the element values of the reference data. The generation module 240 can also use the cross-correlation method to determine the zero-normalized cross-correlation (ZNCC) based on the element values of the corrected signal, the element values of the reference data, the first average value, and the second average value. The generation module 240 can also specify the ZNCC as the cross-correlation coefficient between the corrected signal and the reference data. The cross-correlation coefficient is in the form of a complex number including phase information and amplitude information. In some embodiments, in order to determine the phase offset between the corrected signal and the reference data based on the cross-correlation coefficient, the generation module 240 can specify the value obtained by dividing the cross-correlation coefficient by the modulus of the cross-correlation coefficient as the phase offset between the corrected signal and the reference data.

[0107] Furthermore, the generation module 240 can reconstruct the merged image.

[0108] In some embodiments, the generation module 240 can also generate the merged image based on the corrected signal through any feasible preset merging method.

[0109] The target image refers to the phase image after channel merging, which can reflect the phase information of multiple channel coils.

[0110] In some embodiments, the generation module 240 can determine the target image based on the merged image obtained by multi-channel merging of multiple sets of corrected signals. For example, the generation module 240 can perform multi-channel merging on the relevant information (such as intensity information, phase information, etc.) of multiple sets of corrected signals corresponding to multiple channel coils, reconstruct to obtain the merged image, and then perform a phase extraction operation on the merged image to obtain the target image. Exemplarily, the phase extraction operation can include inverse trigonometric function extraction. The information of one or more pixel points of the merged image is in the form of a complex number, and the phase information of the foregoing one or more pixel points can be obtained through the phase extraction operation.

[0111] In some embodiments of this specification, based on the corrected signal, by means of a preset merging method, by correcting the phase offset of each channel, it helps to eliminate the phase difference between different channels, and further improve the signal-to-noise ratio of the merged image. In some embodiments of this specification, performing calculations based on complex signals helps to obtain a clearer and more accurate target image.

[0112] In some embodiments of this specification, the processing device can acquire multiple sets of echo signals, generate a field distribution map based on the multiple sets of echo signals, and determine the baseline phase map of multiple channel coils through the field distribution map; perform phase correction on the multiple sets of echo signals based on the baseline phase map to obtain multiple sets of corrected signals; perform multi-channel merging on the multiple sets of corrected signals to determine the merged image. In this process, all operations are performed on complex signals, and the merged image is only generated at the end. It can make full use of the information of complex signals about tissue structure and physical properties, which helps to obtain a more accurate image with a better signal-to-noise ratio; in addition, performing all operations on complex signals helps to reduce the amount of calculation and improve the calculation efficiency.

[0113] It should be noted that the above description of process 300 is only for illustration and explanation, and does not limit the scope of application of this specification. For those skilled in the art, various modifications and changes can be made to process 300 under the guidance of this specification. However, these modifications and changes are still within the scope of this specification.

[0114] Figure 4 is an exemplary flowchart of a method for determining a baseline phase map according to some embodiments of this specification. In some embodiments, process 400 can be executed by Figure 2 the system 200 shown, or can be implemented in Figure 1 the application scenario 100 shown. As Figure 4 shown, process 400 includes the following steps.

[0115] Step 410, acquire multiple sets of candidate complex echo signals.

[0116] Candidate complex echo signals refer to magnetic resonance signals that are not from the same source as the aforementioned complex echo signals. The aforementioned complex echo signals refer to the complex echo signals that have been obtained before acquiring the candidate complex echo signals. Not from the same source means different data sources. For example, the candidate complex echo signals and the aforementioned complex echo signals are magnetic resonance signals from different physical positions or different tissue structures. Another example is that the candidate complex echo signals and the aforementioned complex echo signals are magnetic resonance signals obtained by different radio frequency pulse sequences scanning the same object. Among them, the aforementioned complex echo signals and the candidate complex echo signals are different-source data collected by the same coil.

[0117] In some embodiments, the processing device may utilize a magnetic resonance scanning device to apply a radio frequency pulse sequence different from that used when acquiring the foregoing multiple sets of echo signals, and scan the object, and then acquire multiple sets of candidate complex echo signals corresponding to multiple channel coils through the same coil of the magnetic resonance scanning device.

[0118] Step 420: Based on the multiple sets of candidate complex echo signals, determine the baseline phase maps of the multiple channel coils based on complex number calculations.

[0119] In some embodiments, the processing device may determine a field distribution map based on the multiple sets of candidate complex echo signals, and determine the baseline phase maps of the respective channel coils based on the field distribution map. For example, the processing device may, based on the multiple sets of the foregoing complex echo signals, through Steps 310 and 320, determine the filtered field distribution map Θ corresponding to the multiple sets of the foregoing complex echo signals. smooth The processing device may, based on the filtered field distribution map Θ corresponding to the multiple sets of the foregoing complex echo signals smooth and the multiple sets of candidate complex echo signals, determine the baseline phase maps of the multiple channel coils in a manner similar to Formula (3). The processing device may remove the baseline phase signals of the multiple sets of candidate complex echo signals based on the baseline phase maps, and obtain the corrected signals in a manner similar to Formula (4). The processing device may determine the merged image based on the corrected signals through any one of the preset merging methods. For more descriptions of Formula (3), Formula (4), and the preset merging method, reference may be made to Figure 3 the relevant descriptions.

[0120] In some embodiments, each set of candidate complex echo signals includes at least one candidate complex echo signal, and the processing device determines the baseline phase map of the corresponding channel based on the phase information of the at least one candidate complex echo signal.

[0121] In some embodiments, the processing device may acquire the foregoing complex echo signals and candidate complex echo signals of at least one channel coil using gradient echo (GRE), spin echo (SE), steady state free precession (SSFP), etc. The processing device may acquire the foregoing complex echo signals and candidate complex echo signals of at least one channel coil using any other magnetic resonance sequence.

[0122] In some embodiments, when the processing device acquires the foregoing complex echo signals and candidate complex echo signals by means of spin echo or steady-state free precession, the processing device may acquire at least one of the foregoing complex echo signals and candidate complex echo signals through a plurality of channel coils, and determine a field distribution map based on the phase information of at least one of the foregoing complex echo signals and candidate complex echo signals. For example, each channel coil of the plurality of channel coils may acquire only one of the foregoing complex echo signals and candidate complex echo signals, and the phase of the foregoing complex echo signal and candidate complex echo signal can reflect the magnetic field distribution of the channel coil.

[0123] In some embodiments, the foregoing complex echo signals and candidate complex echo signals of at least one channel coil acquired by the processing device by means of spin echo or steady-state free precession are filtered in the complex domain to determine the foregoing complex echo signals after filtering for the channel coil. The processing device may perform baseline phase correction on at least one candidate complex echo signal of the same channel coil based on the foregoing complex echo signals after filtering for the channel coil. For example, for the foregoing complex echo signals of the m-th channel coil of the foregoing complex echo signals acquired by means of spin echo or steady-state free precession, smoothing filtering processing is performed in the complex domain, and the processing device may obtain the foregoing complex echo signals after filtering for the channel coil S smooth,m , and then based on the complex echo signals of the n-th echo of the m-th channel of the candidate complex echo signals, through complex calculation with S smooth,m of the m-th channel, an echo signal S' after baseline phase correction is obtained m,n . Exemplary complex calculation method: is the conjugate complex number of S smooth,m . The processing device may determine a merged image based on the echo signal S' after baseline phase correction m,n in a manner similar to step 340.

[0124] In some embodiments of this specification, the acquisition methods of candidate complex echo signals include spin echo acquisition and steady-state free precession acquisition. In this case, the processing device may determine a baseline phase map of the corresponding channel based on the phase information of at least one candidate complex echo signal, which can effectively improve the calculation speed.

[0125] In some embodiments of this specification, the processing device may acquire multiple groups of candidate complex echo signals, determine baseline phase maps of a plurality of channel coils based on the multiple groups of candidate complex echo signals, and by using different source data, more comprehensive information can be obtained, so as to better estimate the corrected signal, which helps to reduce artifacts and noise and improve the contrast and resolution of the image.

[0126] Experiments on the technical solutions disclosed in some embodiments of this specification have achieved satisfactory results. Some of the results are as Figure 5 and Figure 6 shown.

[0127] Figure 5 are exemplary schematic diagrams of the original phase diagrams, baseline phase diagrams, and corrected phase diagrams of each channel shown in some embodiments of this specification.

[0128] Figure 5 includes the original phase diagram A of each channel, the baseline phase diagram B corresponding to the original phase diagram A, and the corrected phase diagram C. The phase obtained by directly adding the original phase diagrams A of each channel complexly and then taking the phase is the phase diagram A1. The phase obtained by directly adding the corrected phase diagrams C of each channel complexly and then taking the phase is the phase diagram C1. It can be seen from Figure 5 that compared with the original phase diagram A, the baseline phases of each channel are effectively removed in the corrected phase diagram C, significantly improving the phase consistency between channels. The technical solutions disclosed in some embodiments of this specification can make full use of the information of the complex signals of multiple channels of a magnetic resonance imaging coil, thereby helping to obtain a more accurate phase image with a better signal-to-noise ratio.

[0129] Figure 6 are exemplary schematic diagrams of the phase diagrams of each channel and the merged phase diagram shown in some embodiments of this specification.

[0130] Figure 6 includes the phase diagram D of each channel, the phase diagram E of failed channel merging, and the phase diagram F of successful channel merging. The phase diagram E of failed channel merging is the phase image obtained by directly adding the original phase diagrams of each channel complexly. The phase diagram E of failed channel merging includes singularity artifacts and a decrease in signal-to-noise ratio (such as regions E1 and E2). The phase diagram F of successful channel merging is the phase image obtained after being processed by the above-mentioned medical scan data processing method. The phase diagram F of successful channel merging has no singularity artifacts and has a high signal-to-noise ratio.

[0131] Some embodiments of this specification also provide a medical scan data processing device. The device at least includes a processor and a memory. The memory is used to store instructions. When the instructions are executed by the processor, the device is enabled to implement the aforementioned medical scan data processing method.

[0132] Some embodiments of this specification also provide a computer-readable storage medium. The storage medium stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer implements the aforementioned medical scan data processing method.

[0133] The beneficial effects that this application may bring include, but are not limited to: (1) All operations are performed on complex signals, and the combined phase image is generated only at the end, making full use of the information of complex signals about tissue structure and physical properties to obtain a more accurate phase image with better signal-to-noise ratio. (2) The amount of calculation is reduced, and the calculation efficiency is improved.

[0134] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only an example and does not constitute a limitation to this specification. Although not explicitly stated here, those skilled in the art may make various modifications, improvements, and corrections to this specification. Such modifications, improvements, and corrections are suggested in this specification, so such modifications, improvements, and corrections still fall within the spirit and scope of the exemplary embodiments of this specification.

[0135] Meanwhile, this specification uses specific terms to describe the embodiments of this specification. Such as "one embodiment", "an embodiment", and / or "some embodiments" mean a certain feature, structure, or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that the "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more at different positions in this specification does 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.

[0136] In addition, unless clearly stated in the claims, the order of the processing elements and sequences, the use of numbers and letters, or the use of other names in this specification are not used to limit the order of the processes and methods in this specification. Although some currently considered useful embodiments of the invention are discussed through various examples in the above disclosure, it should be understood that such details only serve the purpose of illustration. The appended claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that conform to the essence and scope of the embodiments of this specification. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only through software solutions, such as installing the described system on existing servers or mobile devices.

[0137] Similarly, it should be noted that, in order to simplify the expression of the disclosure of this specification and thus help the understanding of one or more embodiments of the invention, in the description of the embodiments of this specification above, sometimes multiple features are merged into one embodiment, drawing, or description thereof. However, this disclosure method does not mean that the features required by the object of this specification are more than those mentioned in the claims. In fact, the features of the embodiments are fewer than all the features of the single embodiments disclosed above.

[0138] In some embodiments, numbers are used to describe components and quantitative attributes. It should be understood that such numbers used in the description of embodiments are modified by the modifiers "about", "approximate" or "substantially" in some examples. Unless otherwise specified, "about", "approximate" or "substantially" indicate that the said numbers allow a variation of ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may vary according to the characteristics required by individual embodiments. In some embodiments, the numerical parameters should consider the specified significant digits and adopt the method of retaining the general number of digits. Although the numerical ranges and parameters used in some embodiments of this specification to confirm the breadth of their scope are approximate values, in specific embodiments, such numerical settings are as precise as possible within the feasible range.

[0139] For each patent, patent application, patent application publication and other materials cited in this specification, such as articles, books, specifications, publications, documents, etc., their entire contents are hereby incorporated into this specification by reference. Except for the application history documents that are inconsistent with or conflict with the content of this specification, and also except for the documents that limit the broadest scope of the claims of this specification (currently or subsequently attached to this specification). It should be noted that if there are inconsistencies or conflicts between the descriptions, definitions, and / or uses of terms in the supplementary materials of this specification and the content described in this specification, the descriptions, definitions, and / or uses of terms in this specification shall prevail.

[0140] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, by way of example and not limitation, alternative configurations of the embodiments of this specification may be considered to be consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. A method for processing medical scan data, characterized in that, The method includes: Obtaining multiple sets of echo signals, where the multiple sets of echo signals correspond to multiple channel coils; Generating a field distribution map based on the multiple sets of echo signals, and determining a baseline phase map of the multiple channel coils through the field distribution map; Performing phase correction on the multiple sets of echo signals based on the baseline phase map to obtain multiple sets of corrected signals; Performing multi-channel merging based on the multiple sets of corrected signals to determine a merged image.

2. The method according to claim 1, wherein The echo signals are complex signals.

3. The method according to claim 1, characterized in that The obtaining method of each set of echo signals in the multiple sets of echo signals includes: Obtaining echo signals of multiple echoes with different echo times and the same or different echo intervals.

4. The method according to claim 3, characterized in that, The echo signals include at least two dimensions of the echo time and the channel coil. The generating a field distribution map based on the multiple sets of echo signals includes: Using multiple sets of complex echo signals collected by the multiple channel coils at multiple echo times, calculating the field distribution map through a complex method of multi-echo imaging; or Using multiple sets of complex echo signals collected by the multiple channel coils at multiple echo times, extracting the phases of the corresponding multiple sets of echo signals, and calculating the field distribution map through a fitting method.

5. The method according to claim 2, wherein The determining a baseline phase map of the multiple channel coils through the field distribution map includes: Obtaining multiple sets of candidate complex echo signals, where the multiple sets of candidate complex echo signals correspond to multiple channel coils; Based on the multiple sets of candidate complex echo signals, determining the baseline phase map based on complex calculation.

6. The method according to claim 5, characterized in that Each set of candidate complex echo signals in the multiple sets of candidate complex echo signals includes at least one candidate complex echo signal. The method further includes: Based on the phase information of the at least one candidate complex echo signal, determining the baseline phase map of the corresponding channel.

7. The method according to claim 1, characterized in that The performing multi-channel merging based on the multiple sets of corrected signals to determine a merged image includes: Based on the multiple sets of corrected signals, generating the merged image through a preset merging method, where the preset merging method includes one or more of direct complex addition merging, complex weighting merging, and correlation calculation methods; Based on the merged image, determining a target image.

8. A medical scan data processing system, characterized in that, Including an acquisition module, a determination module, a correction module, and a generation module; The acquisition module is used to obtain multiple sets of echo signals, where the multiple sets of echo signals correspond to multiple channel coils; The determination module is used to generate a field distribution map based on the multiple sets of echo signals, and determine a baseline phase map of the multiple channel coils through the field distribution map; The correction module is used to perform phase correction on the multiple sets of echo signals based on the baseline phase map to obtain multiple sets of corrected signals; The generation module performs multi-channel merging based on the multiple sets of corrected signals to determine a merged image.

9. A medical scan data processing device, characterized in that, The device includes at least one processor and at least one memory; The at least one memory is used to store computer instructions; The at least one processor is used to execute at least part of the computer instructions to implement the method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores computer instructions, and when a computer reads the computer instructions in the storage medium, the computer executes the method according to any one of claims 1-7.

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