Blood oxygen level dependent signal processing method and device and electronic device

Abstract

The invention relates to a blood oxygen level dependent signal processing method and device and an electronic device.The processing method comprises the steps that a set of multi-echo signals corresponding to different echo time dimensions under excitation of a multi-echo EPI sequence are obtained, and the set of multi-echo signals correspond to single scanning; performing image reconstruction processing on the group of multi-echo signals to generate a multi-echo image; and performing blood oxygen level dependent signal extraction processing on the multi-echo image to generate a target blood oxygen level dependent signal. According to the method and the device, the problem of low accuracy of blood oxygen level dependent measurement is solved, and the accurate and efficient blood oxygen level dependent signal processing method is realized.

Description

Technical Field

[0001] The present application relates to the field of magnetic resonance technology, and in particular to a method, device and electronic device for processing blood oxygen level dependent signals. Background Art

[0002] With the development of medical technology, magnetic resonance imaging (MRI) technology is becoming more and more important. MRI is a routine procedure for diagnosing and treating various diseases and injuries. It can accurately reflect the pathological tissue conditions, allowing doctors to make accurate diagnoses and provide targeted treatment for patients based on the results of MRI.

[0003] However, in related technologies, due to the constraints of factors such as spatial encoding, the scanning time of the MRI system is relatively long. Especially for multi-echo sequences, after a radio frequency pulse excitation, multiple echoes will be collected through the radio frequency receiving coil, thereby obtaining multiple images with different contrasts or different weights, resulting in a multiple increase in scanning time; the slower imaging speed makes the multi-echo sequence more sensitive to the movement of the subject, and is prone to motion artifacts, thereby reducing the quality of the reconstructed image, and ultimately affecting clinical diagnosis, making the accuracy of blood oxygen level dependent measurements low.

[0004] Currently, no effective solution has been proposed for the problem of low accuracy of blood oxygen level dependent measurements in related technologies. Summary of the invention

[0005] The embodiments of the present application provide a method, device and electronic device for processing a blood oxygen level dependent signal, so as to at least solve the problem of low accuracy of blood oxygen level dependent measurement in the related art.

[0006] In a first aspect, an embodiment of the present application provides a method for processing a blood oxygen level dependent signal, the method comprising: acquiring a group of multi-echo signals corresponding to different echo time dimensions under excitation of a multi-echo echo planar imaging (EPI) sequence, wherein the group of multi-echo signals corresponds to a single scan;

[0007] Performing image reconstruction processing on the group of multi-echo signals to generate a multi-echo image;

[0008] A blood oxygen level dependent signal extraction process is performed on the multi-echo image to generate a target blood oxygen level dependent signal.

[0009] In some embodiments, the set of multi-echo signals forms a two-dimensional K-space data set or a three-dimensional K-space data set, and performing image reconstruction processing on the set of multi-echo signals to generate a multi-echo image includes:

[0010] Image reconstruction processing is performed on the two-dimensional K-space data set or the three-dimensional K-space data set to generate the multi-echo image.

[0011] In some embodiments, the step of acquiring a group of multi-echo signals corresponding to different echo time dimensions under the excitation of a multi-echo EPI sequence includes:

[0012] Collect multiple sequence data corresponding to different echo time dimensions under the same RF pulse excitation;

[0013] The placement position corresponding to the sequence data is determined based on the echo time dimension, a sequence characteristic diagram including all the sequence data is generated based on the placement position, and the multi-echo sequence data is obtained according to the sequence characteristic diagram; wherein the sequence data corresponding to different echo time dimensions have different placement positions in the sequence characteristic diagram.

[0014] In some embodiments, performing image reconstruction processing on the set of multi-echo signals to generate a multi-echo image includes:

[0015] The group of multi-echo signals is filled according to the echo time dimension to obtain a K-space data set, and image reconstruction processing is performed on the K-space data set to generate the multi-echo image.

[0016] In some embodiments, the step of performing blood oxygen level dependent signal extraction processing on the multi-echo image to generate a target blood oxygen level dependent signal includes:

[0017] Performing neuron signal fitting processing on the blood oxygen level dependent signal of each voxel point in the multi-echo image to obtain a corresponding signal fitting value;

[0018] The multi-echo image is subjected to noise filtering processing based on the signal fitting value, and the target blood oxygen level dependent signal is extracted.

[0019] In some embodiments, the step of performing blood oxygen level dependent signal extraction processing on the multi-echo image to generate a target blood oxygen level dependent signal includes:

[0020] Performing time attenuation curve fitting processing on each voxel point in the multi-echo image to obtain a relaxation time weight value corresponding to each frame of the multi-echo image;

[0021] The multi-echo images are weightedly fused based on the relaxation time weight value to obtain a fused echo image, and a blood oxygen level dependent signal extraction process is performed on the fused echo image to generate the target blood oxygen level dependent signal.

[0022] In a second aspect, an embodiment of the present application provides a device for processing a blood oxygen level dependent signal, the device comprising: an acquisition module, a reconstruction module, and a generation module;

[0023] The acquisition module is used to acquire a group of multi-echo signals corresponding to different echo time dimensions under the excitation of the multi-echo EPI sequence, wherein the group of multi-echo signals corresponds to a single scan;

[0024] The reconstruction module is used to perform image reconstruction processing on the group of multi-echo signals to generate a multi-echo image;

[0025] The generating module is used to perform blood oxygen level dependent signal extraction processing on the multi-echo image to generate a target blood oxygen level dependent signal.

[0026] In some embodiments, the group of multi-echo signals forms a two-dimensional K-space dataset or a three-dimensional K-space dataset, and the reconstruction module is further used to perform image reconstruction processing on the two-dimensional K-space dataset or the three-dimensional K-space dataset to generate the multi-echo image.

[0027] In a third aspect, an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for processing blood oxygen level dependent signals as described in the first aspect above is implemented.

[0028] In a fourth aspect, an embodiment of the present application provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for processing a blood oxygen level dependent signal as described in the first aspect above.

[0029] Compared with the related art, the blood oxygen level dependent signal processing method, device and electronic device provided in the embodiments of the present application obtain a group of multi-echo signals corresponding to different echo time dimensions under the excitation of a multi-echo EPI sequence, and the group of multi-echo signals corresponds to a single scan; image reconstruction processing is performed on the group of multi-echo signals to generate a multi-echo image; blood oxygen level dependent signal extraction processing is performed on the multi-echo image to generate a target blood oxygen level dependent signal, which solves the problem of low accuracy of blood oxygen level dependent measurement and realizes an accurate and efficient blood oxygen level dependent signal processing method.

[0030] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0032] Figure 1 is an application environment diagram of a method for processing a blood oxygen level dependent signal according to an embodiment of the present application;

[0033] Figure 2 is a flow chart of a method for processing a blood oxygen level dependent signal according to an embodiment of the present application;

[0034] Figure 3 is a schematic diagram of a multi-echo signal sequence according to an embodiment of the present application;

[0035] Figure 4 is a schematic diagram of another multi-echo signal sequence according to an embodiment of the present application;

[0036] Figure 5 is a characteristic schematic diagram of a multi-echo signal sequence according to an embodiment of the present application;

[0037] Figure 6 is a schematic diagram of a neuron activity-specific signal according to an embodiment of the present application;

[0038] Figure 7 is a schematic diagram of a noise signal according to an embodiment of the present application;

[0039] Figure 8 is a schematic diagram of an echo signal according to an embodiment of the present application;

[0040] Fig. 9 is a schematic diagram of an echo image according to an embodiment of the present application;

[0041] Fig.10 is a structural block diagram of a device for processing a blood oxygen level dependent signal according to an embodiment of the present application;

[0042] Fig.11 It is a structural diagram of the inside of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application. In addition, it can also be understood that although the efforts made in this development process may be complex and lengthy, for ordinary technicians in the field related to the contents disclosed in the present application, some changes such as design, manufacturing or production based on the technical contents disclosed in the present application are only conventional technical means, and should not be understood as insufficient contents disclosed in the present application.

[0044] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those of ordinary skill in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0045] Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the" and the like involved in this application do not indicate a quantitative limitation, and may represent the singular or plural. The terms "include", "comprise", "have" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to greater than or equal to two. "And / or" describes the association relationship of associated objects, indicating that there can be three relationships, for example, "A and / or B" can represent: A exists alone, A and B exist at the same time, and B exists alone. The terms "first", "second", "third" and the like involved in the present application are merely used to distinguish similar objects and do not represent a specific ordering of the objects.

[0046] The blood oxygen level dependent signal processing method provided in this application can be applied to Figure 1In the application environment shown. The application environment may include a terminal device 101 and a magnetic resonance device 102. The terminal 101 may communicate with the magnetic resonance (MR) device 102 via a network. The terminal device 101 may be, but is not limited to, various personal computers, laptop computers, and tablet computers. The application environment may also include a server device 103, and both the terminal 101 and the magnetic resonance device 102 may communicate with the server device 103 via a network. The server device 103 may be implemented with an independent server or a server cluster consisting of multiple servers.

[0047] Specifically, the magnetic resonance device 102 includes a magnetic resonance scanner and a scanning bed coupled to the magnetic resonance scanner. The magnetic resonance scanner forms a scanning cavity, and the scanning bed is used to support the detection object. The scanning bed can be moved and move the detection object into the scanning cavity. A surface receiving coil can be placed on the body surface of the detection object, and the surface receiving coil can enter or move out of the scanning cavity with the detection object, and the surface receiving coil can receive the magnetic resonance signal excited by the detection object in the scanning cavity.

[0048] The magnetic resonance scanner includes a magnet module and a radio frequency transmission module. The magnet module may include a magnet and a gradient magnetic field generator. The magnet may generate a static magnetic field B0 during the MRI process. The magnet may be of various types, including, for example, a permanent magnet, a superconducting electromagnet, a resistive electromagnet, etc. The gradient magnetic field generator may generate a magnetic field gradient to the main magnetic field B0 in the X, Y or Z direction. The gradient magnetic field may encode spatial information of an object located in the magnetic resonance scanner. The radio frequency transmission module may transmit an RF signal to an object of interest.

[0049] In some embodiments, the function, size, type, geometry, position, amount, and / or amplitude of the magnet module and / or the RF transmission module may be determined or changed according to one or more specific conditions. In some embodiments of the present disclosure, the RF transmission module may include a birdcage coil, a transverse electromagnetic coil, a surface coil, a saddle coil, etc. In some embodiments, the magnet module and the RF transmission module may be designed to surround the object to form a tunnel type or an open type.

[0050] This embodiment provides a method for processing a blood oxygen level dependent signal. Figure 2 is a flow chart of a method for processing a blood oxygen level dependent signal according to an embodiment of the present application, such as Figure 2 As shown, the process includes the following steps:

[0051] Step S210 , obtaining a group of multi-echo signals corresponding to different echo time dimensions under EPI sequence excitation, where the group of multi-echo signals corresponds to a single scan.

[0052] Among them, echo planar imaging EPI is a special form of gradient echo. It uses a fast reverse gradient to generate a series of gradient echoes within a single repetition time (Repetition Time, TR) and phase encodes them respectively, fills them into the corresponding K space, and realizes cross-sectional imaging. Specifically, EPI is developed on the basis of gradient echo, and the MR signal collected by EPI also belongs to the gradient echo signal. The general gradient echo is to generate a gradient echo by a positive and negative switching of the readout gradient field (i.e., the frequency encoding gradient field) after a radio frequency pulse excitation; the difference of EPI technology is that it uses the continuous positive and negative switching of the readout gradient field, and each switching generates a gradient echo, thereby generating multiple gradient echoes, which can be understood as a radio frequency pulse excitation to collect multiple gradient echoes. In this embodiment, what is obtained is a multi-pulse sequence under a single scan, that is, a group of multi-echo signals of a single scan are sorted according to the corresponding echo time dimension for subsequent processing.

[0053] Step S220: performing image reconstruction processing on the group of multi-echo signals to generate a multi-echo image.

[0054] Among them, the above-mentioned group of multi-echo signals is image reconstructed based on the above-mentioned different echo time dimensions to generate a multi-echo image. Specifically, by utilizing the similarity and slowly changing characteristics between images with different echo times, as well as the sparsity of the image itself in the sparse domain, the group of multi-echo signals can be reconstructed using an algorithm based on low rank or compressed sensing, and the unknown data of the K echo space can be filled to finally obtain a multi-echo image. It should be supplemented that, compared with the image reconstruction method in the related art, which is usually to reconstruct signals with different echo times in the same frame image, the embodiment of the present application can reconstruct an image at each data reading through the above steps, so that a large number of echo images can be finally obtained through multi-pulse sequence reconstruction under a single scan, and the echo time between adjacent echo images differs only by an echo interval; the echo interval is usually less than 1ms; at the same time, since the signals in each image are from the same echo time, they are not affected by the image distortion caused by the attenuation of the transverse relaxation time and the inhomogeneity of the magnetic field, thereby ensuring that the reconstructed image is not deformed.

[0055] Step S230 , performing blood oxygen level dependent signal extraction processing on the multi-echo image to generate a target blood oxygen level dependent signal.

[0056] Among them, a single gradient echo functional magnetic resonance imaging (functional MRI, fMRI for short) image usually contains a blood oxygen level dependent signal caused by changes in blood oxygen level and a noise signal generated by the movement or breathing changes of the object to be examined. In this embodiment, by acquiring multiple gradient echo images, the echo time decay curve fitting can be performed for the signal of a single voxel at a single time point, and finally the non-Gaussian noise signal that is independent of the echo time can be stripped out, the blood oxygen level dependent signal "denoising" function is realized, and the above-mentioned target blood oxygen level dependent signal is obtained, thereby effectively improving the fMRI imaging specificity.

[0057] Through the above steps, by acquiring multi-echo sequence data of different echo time dimensions under a single scan, image reconstruction is performed on the multi-echo sequence data to obtain a multi-echo image, and finally the blood oxygen level dependent measurement value is calculated based on the multi-echo image, thereby realizing the blood oxygen level dependent measurement method that takes into account the echo space and reconstructs at the same time, so that after the reconstruction is completed, multiple echo images are obtained at the same time for calculation, and more different echo time images can be obtained through one scan, thereby improving the signal-to-noise ratio and noise robustness of the blood oxygen level dependent signal, effectively solving the problem of low accuracy of blood oxygen level dependent measurement, and realizing an accurate and efficient blood oxygen level dependent signal processing method.

[0058] In some embodiments, the above-mentioned group of multi-echo signals forms a two-dimensional K-space dataset or a three-dimensional K-space dataset; the above-mentioned image reconstruction processing of the group of multi-echo signals to generate a multi-echo image includes the following steps: performing image reconstruction processing on the two-dimensional K-space dataset or the three-dimensional K-space dataset to generate the multi-echo image.

[0059] Specifically, considering the echo time dimension, the phase encoding of each pulse can be determined after pulse excitation so that the pulse can cover a certain range in the K echo space. For example, Figure 3 is a schematic diagram of a multi-echo signal sequence according to an embodiment of the present application, such as Figure 3As shown, RF represents the radio frequency transmission signal; Gz represents the magnetic field gradient formed in the Z direction, which is called the slice selection gradient; Gy represents the magnetic field gradient in the Y direction, which is called the phase encoding gradient; Gx represents the gradient in the X direction, which is called the frequency readout gradient. At this time, phase encoding is performed on the two-dimensional data collected in the X and Y directions and without the collected signal in the Z direction; specifically, different pulse phase encodings are designed under each pulse excitation to obtain the above-mentioned two-dimensional K-space data set. Next, the acquired two-dimensional K-space data set is reconstructed using algorithms such as compressed sensing, and finally the above-mentioned multi-echo image is obtained. In this embodiment, after a single RF pulse excitation, a series of gradient lobes are applied along the Gy gradient axis. Specifically, a series of frequency encoding gradients with reversed polarity are applied on the Gx gradient axis, and a gradient lobe (blip) is applied on the Gy gradient axis after the polarity of the frequency encoding gradient is reversed, and different blip pulses are applied at different positions. In this embodiment, the polarities or intensities of two adjacent blip pulses applied in sequence are different, or the polarities and intensities of two adjacent blip pulses are different, which causes the sampling signal to fill a non-fixed distance in the k-space and form a random sampling trajectory.

[0060] In another embodiment, Figure 4 is a schematic diagram of another multi-echo signal sequence according to an embodiment of the present application, such as Figure 4 As shown, at this time, pulse encoding is performed for the three-dimensional data collected in the X direction, Y direction and Z direction, that is, phase encoding is performed for the signal in the Gy direction, and the same designable encoding method as the Gy direction is used for the signal in the Gz direction; through multiple pulse excitations and data acquisition, the height reduction data in the three-dimensional K echo space is obtained, and then the three-dimensional K space data set is image reconstructed. In this embodiment, after a single RF pulse excitation, a series of gradient lobes are applied simultaneously along the Gz and Gy gradient axes. Specifically, a series of frequency encoding gradients with polarity reversal are applied on the Gx gradient axis, and after the polarity of the frequency encoding gradient is reversed, gradient lobes (blips) are applied on the Gy and Gz gradient axes, and the blip pulses applied at different positions are different. Through the above embodiment, the image reconstruction processing is performed on the two-dimensional K space data set or the three-dimensional K space data set collected by encoding, so that the height reduction trajectory finally formed can have sufficient low-frequency signals covering the center of the K space, and a small amount of high-frequency signals randomly distributed and covering the surrounding of the K space, which is conducive to improving the accuracy of image reconstruction.

[0061] In some embodiments, the above-mentioned step of acquiring a group of multi-echo signals corresponding to different echo time dimensions under the excitation of a multi-echo EPI sequence includes the following steps:

[0062] Step S211 , collecting a plurality of sequence data corresponding to different echo time dimensions under the same pulse excitation.

[0063] In this embodiment, the echo time dimension is taken into consideration, and a large number of EPI images with different echo times are obtained through a single scan, that is, the above-mentioned sequence data is obtained.

[0064] Step S212, determining the placement position corresponding to the sequence data based on the echo time dimension, generating a sequence characteristic diagram including all the sequence data based on the placement position, and obtaining the multi-echo sequence data according to the sequence characteristic diagram; wherein the sequence data corresponding to different echo time dimensions have different placement positions in the sequence characteristic diagram.

[0065] In this embodiment, the signals acquired at different echo times are placed separately in the corresponding sequence feature graph, so as to add an echo time dimension on the basis of the traditional K-space signal. Figure 5 Taking two pulse excitations as an example, the sequence data under the two pulse excitations are sorted and placed according to different echo times, that is, separated by the echo time interval on the horizontal axis and separated by the phase encoding gradient on the vertical axis, so that based on the echo time dimension, a larger echo time range, smaller echo interval and more image groups can be reconstructed.

[0066] Through the above steps S211 to S212, the time dimension is taken into consideration when designing the multi-pulse EPI sequence, so that a zero deformation image with a shorter echo time can be obtained, which is beneficial for subsequent steps to obtain a more accurate blood oxygen level dependent signal image, further improving the accuracy of blood oxygen level dependent signal extraction.

[0067] In some of the embodiments, the above-mentioned image reconstruction processing of the group of multi-echo signals to generate a multi-echo image includes the following steps: filling the group of multi-echo signals according to the echo time dimension to obtain a K space data set, and performing image reconstruction processing on the K space data set to generate the multi-echo image. Among them, random coding can be used, and the image can be reconstructed based on a low-rank or compressed sensing method. Specifically, taking the above-mentioned reconstruction method using a compressed sensing algorithm as an example, a compressed sensing algorithm can be used to reconstruct the group of multi-echo signals according to the echo time dimension, and based on the low rank of the echo time dimension, fill the unknown data of the K echo space. It should be supplemented that the low rank of the above-mentioned echo time dimension means that the signal generated at a certain spatial position changes regularly with the echo time.

[0068] Alternatively, in another embodiment, the above image reconstruction method can also be: when the encoding method is designed to make the K echo space uniformly downsampled, that is, the style of the collected data is repetitive, for example, for the two-dimensional echo space, the downsampling formula of each 16×16×4 space can be made the same, and it is defined as the reconstruction kernel, and finally the same style is used to combine into a global downsampling formula of 256×256×48, a linear reconstruction method using the generalized autocalibrated partially parallel acquisition (GRAPPA) algorithm as an example can be used to reconstruct based on the above echo time dimension. Specifically, firstly, the full sampling data in a small part of the K echo space area (usually the central area of ​​the K space) is collected, and the pattern of obtaining unknown points based on known points in the above reconstruction kernel is learned, and the reconstructed image can be obtained after the pattern is traversed and convolved on the highly downsampled data.

[0069] In some embodiments, the above-mentioned blood oxygen level dependent signal extraction processing is performed on the multi-echo image to generate a target blood oxygen level dependent signal, including the following steps:

[0070] Step S231 , performing neuron signal fitting processing on the blood oxygen level-dependent signal of each voxel point in the multi-echo image to obtain a corresponding signal fitting value.

[0071] It should be noted that the collected single gradient echo fMRI image usually contains the blood oxygen level dependent signal caused by the change of blood oxygen level, and the noise signal caused by the subject's movement or breathing changes. Among them, the blood oxygen level dependent signal reflects the information of neuronal activity, so it needs to be retained as a useful signal; while the noise signal will interfere with the final analysis result. In the related art, it is extremely important to distinguish between neuronal activity and noise signals in the process of imaging the blood oxygen level dependent signal. Therefore, in this embodiment, the signal denoising function is realized by K echo space multi-pulse EPI imaging technology, which can effectively improve the contrast of the blood oxygen level dependent signal.

[0072] The above-mentioned voxel refers to the abbreviation of each volume element for each frame of multi-echo image. Specifically, after acquiring multiple gradient echo images, the echo time decay curve is fitted for the blood oxygen level dependent signal of each single volume pixel point in the multi-echo image. Exemplarily, for the blood oxygen level dependent signal and the noise signal, the signal change percentage before and after the neuron activation satisfies the following respectively: Figure 6 and Figure 7 The signal model shown, i.e., the percentage change of the signal of the neuronal activity-specific signal changes linearly with the echo time, while the percentage change of the signal of the noise signal remains fixed.

[0073] Step S232: performing noise filtering on the multi-echo image based on the signal fitting value, and extracting the target blood oxygen level dependent signal.

[0074] See also Figure 6 and Figure 7 By performing percentage fitting on the signal changes before and after activation of a single voxel, the non-Gaussian noise signal that is independent of the echo time can be stripped out, and only the neuronal activity-specific signal can be extracted to achieve the denoising function of the blood oxygen level-dependent signal, which is beneficial to improve the specificity of fMRI imaging.

[0075] Through the above steps S231 to S232, the multi-echo image is subjected to neuronal signal fitting and noise filtering processing, thereby realizing a signal denoising method based on K-echo space multi-pulse imaging technology, effectively improving the contrast of the blood oxygen level dependent signal, and further improving the accuracy of the blood oxygen level dependent signal extraction.

[0076] In some embodiments, the above-mentioned blood oxygen level dependent signal extraction processing is performed on the multi-echo image to generate a target blood oxygen level dependent signal, including the following steps:

[0077] A time attenuation curve fitting process is performed for each voxel point in the above multi-echo image to obtain the relaxation time weight value corresponding to each frame of the multi-echo image. The above relaxation time weight value is a weight value assigned to different echo images based on the tissue T2* value. Among them, T2* attenuation means that without eliminating the inhomogeneity of the main magnetic field, after a 90° radio frequency pulse, the macroscopic transverse magnetization vector will show an exponentially rapid decay under the influence of two factors of the proton vector phase; this decay is free induction decay, that is, T2* relaxation.

[0078] Next, weighted fusion processing is performed on the multi-echo images based on the relaxation time weight value to obtain a fused echo image, and blood oxygen level dependent signal extraction processing is performed on the fused echo image to generate the target blood oxygen level dependent signal.

[0079] Through the above embodiment, weighted fusion processing is performed on different echo images with reference to the tissue T2* value, so that the signal-to-noise ratio of the image can be further improved, which is conducive to extracting a more accurate and robust blood oxygen level dependent signal.

[0080] The present application is described in detail below in conjunction with actual application scenarios. The above-mentioned blood oxygen level dependent signal processing method includes the following process:

[0081] After obtaining a group of multi-echo signals through the steps in any of the above method embodiments, Figure 3 or Figure 4The sequence shown can be reconstructed by Fourier to obtain N echo images, and the echo time of each echo image increases in sequence. Then each echo image is fitted, and the fitting curve of each echo image corresponds to the signal change law of the echo in the time dimension within a single voxel. In this example, according to the GRE-EPI signal attenuation characteristics, multiple echo signals show T2* exponential attenuation; please refer to Figure 8 In the figure, the horizontal axis represents the TE time, and the vertical axis represents the intensity of the simulation signal; it can be seen that the longer the echo time (TE), the weaker the magnetic resonance signal of the corresponding echo.

[0082] Next, the image signal-to-noise ratio is improved by weighted averaging of each echo data; the noise signal (independent of echo time) and the BOLD signal (dependent on echo time) are stripped out by the signal's dependence on echo time, and the image quality is improved accordingly after the noise signal is removed. In this way, the image quality can be improved through multi-echo data. Specifically, in this embodiment, the multi-echo image is subjected to blood oxygen level dependent signal extraction processing to generate a target blood oxygen level dependent signal, which may include:

[0083] The eight collected echo data are processed with corresponding weight allocation according to the following formula;

[0084]

[0085] Among them, ω TE It represents the weight coefficient corresponding to each TE, TE represents the echo time, and T2* is a constant.

[0086] Considering that the weight of each echo is affected by its own TE value and the T2* value of the tissue, the TE value of each echo is known, and the T2* value needs to be obtained by fitting the signal of each echo. In addition, the eight echo signals show T2* exponential decay, and the decay law conforms to Therefore, according to Formula 2, the T2* value corresponding to each voxel tissue can be fitted, and the weight corresponding to each echo can be obtained by substituting it into Formula 1. Finally, the weight of each echo is approximately Figure 3 . At the same time, S0 can be obtained through fitting.

[0087] See also Fig. 9 , the three-echo images were T2*-weighted averaged to obtain the image TE Comb, and one layer of data was selected to analyze the difference between it and the traditional single-echo image (TE=30ms). Compared with the traditional single-echo BOLD image, the combined image compensates for the signal loss in the skull vertex area caused by field inhomogeneity.

[0088] Further, the magnetic resonance signal of the composite image is subjected to independent component analysis to obtain a plurality of independent component components;

[0089] Furthermore, the BOLD signal can be obtained by performing a noise signal stripping operation on the independent component components;

[0090] In addition, the whole-brain resting-state brain functional network results were obtained based on the BOLD signal.

[0091] Ultimately, the signal attenuation law can be used to distinguish two types of signals from the synthetic image: signal changes that are unrelated to TE (noise signals); signal changes that are related to TE (BOLD signals), thereby realizing an accurate and efficient method for extracting blood oxygen level-dependent signals.

[0092] It should be noted that the steps shown in the above process or the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0093] This embodiment also provides a blood oxygen level dependent signal processing device, which is used to implement the above embodiments and preferred embodiments, and will not be repeated here. As used below, the terms "module", "unit", "subunit", etc. can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.

[0094] Fig.10 is a structural block diagram of a blood oxygen level dependent signal processing device according to an embodiment of the present application, such as Fig.10 As shown, the device includes: an acquisition module 82, a reconstruction module 84 and a generation module 86; the acquisition module 82 is used to acquire a group of multi-echo signals corresponding to different echo time dimensions under the excitation of the multi-echo EPI sequence, and the group of multi-echo signals corresponds to a single scan; the reconstruction module 84 is used to perform image reconstruction processing on the group of multi-echo signals to generate a multi-echo image; the generation module 86 is used to perform blood oxygen level dependent signal extraction processing on the multi-avoidance image to generate a target blood oxygen level dependent signal.

[0095] Through the above embodiment, the acquisition module 82 acquires multi-echo sequence data of different echo time dimensions under a single scan, the reconstruction module 84 performs image reconstruction on the multi-echo sequence data to obtain a multi-echo image, and the final generation module 86 calculates the blood oxygen level dependent measurement value based on the multi-echo image, thereby realizing the consideration of the echo space and simultaneous reconstruction, so that after the reconstruction is completed, a blood oxygen level dependent measurement device that simultaneously obtains multiple echo images for calculation can obtain more images with different echo times through a single scan, thereby improving the signal-to-noise ratio and noise robustness of the blood oxygen level dependent signal, effectively solving the problem of low accuracy of blood oxygen level dependent measurement, and realizing an accurate and efficient blood oxygen level dependent signal processing device.

[0096] In some embodiments, the above-mentioned set of multi-echo signals forms a two-dimensional K-space dataset or a three-dimensional K-space dataset, and the above-mentioned reconstruction module 84 is also used to perform image reconstruction processing on the two-dimensional K-space dataset or the three-dimensional K-space dataset to generate the multi-echo image.

[0097] In some embodiments, the acquisition module 82 is also used to collect multiple sequence data corresponding to different echo time dimensions under the same RF pulse excitation; the acquisition module 82 determines the placement position corresponding to the sequence data based on the echo time dimension, generates a sequence feature graph including all the sequence data based on the placement position, and obtains the multi-echo sequence data according to the sequence feature; wherein the sequence data corresponding to different echo time dimensions have different placement positions in the sequence feature graph.

[0098] In some embodiments, the reconstruction module 84 is further used to fill the first group of multi-echo signals according to the echo time dimension to obtain a K-space data set, and perform image reconstruction processing on the K-space data set to generate the multi-echo image.

[0099] In some embodiments, the generation module 86 is further used to perform neuron signal fitting processing on the blood oxygen level dependence signal of each voxel point in the multi-echo image to obtain a corresponding signal fitting value; the generation module 86 performs noise filtering processing on the multi-echo image based on the signal fitting value, and extracts the target blood oxygen level dependence signal.

[0100] In some embodiments, the above-mentioned generation module 86 is also used to perform time attenuation curve fitting processing on each voxel point in the multi-echo image to obtain a relaxation time weight value corresponding to each frame of the multi-echo image; the generation module 86 performs weighted fusion processing on the multi-echo image based on the relaxation time weight value to obtain a fused echo image, and performs blood oxygen level dependent signal extraction processing on the fused echo image to generate the target blood oxygen level dependent signal.

[0101] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0102] In some embodiments, a computer device is provided, which may be a server. Fig.11 is a structural diagram of the inside of a computer device according to an embodiment of the present application, such as Fig.11 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the target blood oxygen level dependent signal. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the above-mentioned blood oxygen level dependent signal processing method is implemented.

[0103] Those skilled in the art will understand that Fig.11 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0104] This embodiment further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0105] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0106] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0107] S1, obtaining a group of multi-echo signals corresponding to different echo time dimensions under the excitation of a multi-echo EPI sequence, where the group of multi-echo signals corresponds to a single scan.

[0108] S2, performing image reconstruction processing on the group of multi-echo signals to generate a multi-echo image.

[0109] S3, performing blood oxygen level dependent signal extraction processing on the multi-echo image to generate a target blood oxygen level dependent signal.

[0110] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0111] In addition, in combination with the method for processing the blood oxygen level dependent signal in the above embodiment, the embodiment of the present application can provide a storage medium for implementation. The storage medium stores a computer program; when the computer program is executed by the processor, any one of the methods for processing the blood oxygen level dependent signal in the above embodiment is implemented.

[0112] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0113] Those skilled in the art should understand that the technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0114] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for processing a blood oxygen level dependent signal, characterized in that: The method comprises: Acquire a group of multi-echo signals corresponding to different echo time dimensions under the excitation of a multi-echo EPI sequence, wherein the group of multi-echo signals corresponds to a single scan; Performing image reconstruction processing on the group of multi-echo signals to generate a multi-echo image; A blood oxygen level dependent signal extraction process is performed on the multi-echo image to generate a target blood oxygen level dependent signal.

2. The processing method according to claim 1, characterized in that: The group of multi-echo signals forms a two-dimensional K-space data set or a three-dimensional K-space data set, and the image reconstruction processing is performed on the group of multi-echo signals to generate a multi-echo image, including: Image reconstruction processing is performed on the two-dimensional K-space data set or the three-dimensional K-space data set to generate the multi-echo image.

3. The processing method according to claim 1, characterized in that: The step of acquiring a group of multi-echo signals corresponding to different echo time dimensions under the excitation of a multi-echo EPI sequence includes: Collect multiple sequence data corresponding to different echo time dimensions under the same RF pulse excitation; The placement position corresponding to the sequence data is determined based on the echo time dimension, a sequence characteristic diagram including all the sequence data is generated based on the placement position, and the multi-echo sequence data is obtained according to the sequence characteristic diagram; wherein the sequence data corresponding to different echo time dimensions have different placement positions in the sequence characteristic diagram.

4. The processing method according to claim 1, characterized in that: The performing image reconstruction processing on the group of multi-echo signals to generate a multi-echo image comprises: The group of multi-echo signals is filled according to the echo time dimension to obtain a K-space data set, and image reconstruction processing is performed on the K-space data set to generate the multi-echo image.

5. The processing method according to claim 1, characterized in that: The performing blood oxygen level dependent signal extraction processing on the multi-echo image to generate a target blood oxygen level dependent signal includes: Performing neuron signal fitting processing on the blood oxygen level dependent signal of each voxel point in the multi-echo image to obtain a corresponding signal fitting value; The multi-echo image is subjected to noise filtering processing based on the signal fitting value, and the target blood oxygen level dependent signal is extracted.

6. The processing method according to any one of claims 1 to 5, characterized in that: The performing blood oxygen level dependent signal extraction processing on the multi-echo image to generate a target blood oxygen level dependent signal includes: Performing time attenuation curve fitting processing on each voxel point in the multi-echo image to obtain a relaxation time weight value corresponding to each frame of the multi-echo image; The multi-echo images are weightedly fused based on the relaxation time weight value to obtain a fused echo image, and a blood oxygen level dependent signal extraction process is performed on the fused echo image to generate the target blood oxygen level dependent signal.

7. A blood oxygen level dependent signal processing device, characterized in that: The device comprises: an acquisition module, a reconstruction module and a generation module; The acquisition module is used to acquire a group of multi-echo signals corresponding to different echo time dimensions under the excitation of the multi-echo EPI sequence, wherein the group of multi-echo signals corresponds to a single scan; The reconstruction module is used to perform image reconstruction processing on the group of multi-echo signals to generate a multi-echo image; The generating module is used to perform blood oxygen level dependent signal extraction processing on the multi-echo image to generate a target blood oxygen level dependent signal.

8. The processing device according to claim 7, characterized in that The group of multi-echo signals forms a two-dimensional K-space data set or a three-dimensional K-space data set, and the reconstruction module is further used to perform image reconstruction processing on the two-dimensional K-space data set or the three-dimensional K-space data set to generate the multi-echo image.

9. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to execute the method for processing a blood oxygen level dependent signal according to any one of claims 1 to 6.

10. A storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to execute the method for processing a blood oxygen level dependent signal according to any one of claims 1 to 6 when running.

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