Method, system, medium and electronic device for locating ventral intermediate nucleus of thalamus

Abstract

The present invention provides a method, system, medium, and electronic device for locating the ventral intermediate nucleus of the thalamus. The method comprises the following steps: acquiring magnetic resonance multi-echo gradient echo data and non-magnetic field disturbance transverse relaxation rate R2 images of the brain; generating a reconstructed quantitative magnetic susceptibility image based on the magnetic resonance multi-echo gradient echo data; acquiring a paramagnetic magnetic susceptibility image and a diamagnetic magnetic susceptibility image based on the magnetic resonance multi-echo gradient echo data and the non-magnetic field disturbance transverse relaxation rate R2 image; registering the reconstructed quantitative magnetic susceptibility image with the prior quantitative magnetic susceptibility image to acquire the position of the ventral intermediate nucleus of the thalamus; dividing the contour of the ventral intermediate nucleus of the thalamus on the diamagnetic magnetic susceptibility image based on the position of the ventral intermediate nucleus of the thalamus. The method, system, medium, and electronic device for locating the ventral intermediate nucleus of the thalamus of the present invention realize the positioning of the ventral intermediate nucleus of the thalamus based on subvoxel quantitative magnetic susceptibility imaging, thereby improving the positioning efficiency and positioning accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of biomedical engineering, and in particular to a method, system, medium and electronic equipment for locating the ventral intermediate nucleus of the thalamus. Background Art

[0002] The ventralis intermedius nucleus (Vim) is located in the ventral thalamic nucleus, adjacent to the ventral anterior nucleus and ventral posteromedial nucleus. It is approximately elliptical in shape, extending along the anterior-posterior axis, with its axis parallel to the long axis of the cerebral hemisphere. The Vim nucleus receives afferent signals from the bilateral cerebellar dentate nuclei and basal ganglia, and projects this information to the central precentral gyrus. The central precentral gyrus in turn sends feedback impulses to control the electrical activity of the Vim nucleus. Therefore, the Vim nucleus is regarded as a key center for subcortical motor integration. Due to its role in motor regulation, the Vim nucleus is often used as one of the important targets of deep brain stimulation (DBS) surgery for the treatment of drug-refractory essential tremor, tremor caused by Parkinson's disease, and other types of movement disorders. DBS surgery improves the patient's symptoms by implanting electrodes in the Vim nucleus and regulating its neural activity with high-frequency electrical stimulation. In addition, pathological changes in certain neurodegenerative diseases (such as multiple system atrophy) or genetic diseases may affect the function and structure of the Vim nucleus. By accurately locating the Vim nucleus, its volume, morphology, signal intensity, etc. can be quantitatively analyzed, which is of great value for early diagnosis of the disease, monitoring of disease progression, and evaluation of therapeutic efficacy. Therefore, accurate positioning of the Vim nucleus with the help of medical imaging is indispensable for implementing effective clinical intervention, deeply understanding its neurophysiological functions, conducting accurate disease diagnosis and treatment planning, and promoting relevant scientific research progress.

[0003] Magnetic Resonance Imaging (MRI) is a non-invasive medical imaging technology commonly used in clinical practice, which has high resolution and good soft tissue contrast. The anatomical details of the Vim nucleus are not visible on the T1-weighted and T2-weighted MRI structural images routinely collected in clinical practice, and it is difficult to distinguish it from other nearby thalamic nuclei. Therefore, using conventional clinical MRI technology to accurately locate the position of the Vim nucleus and determine the target of surgical treatment is a major challenge currently facing this field. The magnetic resonance phase contrast of human brain tissue can reflect the spatial distribution of magnetic substances such as paramagnetic iron deposition and diamagnetic myelin in the brain. Histological staining experiments have found that the Vim nucleus has a high degree of myelination, and its diamagnetic myelin content is significantly different from that of the surrounding thalamic nuclei. Quantitative Susceptibility Mapping (QSM) technology can obtain the magnetic susceptibility distribution of the whole brain based on the magnetic resonance phase image, effectively quantify the content of the overall magnetic susceptibility source, and is of great value for the precise positioning of the Vim nucleus. Figure 1 The figure shows the location of the ventral intermediate nucleus of the thalamus in T1-weighted images and quantitative magnetic susceptibility images. However, due to the millimeter-level spatial resolution of clinical magnetic resonance, paramagnetic or diamagnetic substances usually coexist in the same voxel, resulting in the magnetic resonance phase image reflecting the effect of paramagnetic and diamagnetic substances canceling each other out. Traditional QSM technology cannot distinguish between the two, resulting in the lack of specificity and reliability of current quantitative results, which brings certain difficulties to the precise positioning of the Vim nucleus. Summary of the invention

[0004] In view of the above-mentioned problems, the purpose of the present invention is to provide a method, system, medium, and electronic equipment for locating the ventral intermediate nucleus of the thalamus, which can realize the positioning of the ventral intermediate nucleus of the thalamus based on subvoxel quantitative magnetic susceptibility imaging, thereby improving the positioning efficiency and positioning accuracy.

[0005] In a first aspect, the present invention provides a method for locating the ventral intermediate nucleus of the thalamus, the method comprising the following steps: acquiring magnetic resonance multi-echo gradient echo data and non-magnetic field disturbance transverse relaxation rate R2 images of the brain; generating a reconstructed quantitative susceptibility image based on the magnetic resonance multi-echo gradient echo data; acquiring a paramagnetic susceptibility image and a diamagnetic susceptibility image based on the magnetic resonance multi-echo gradient echo data and the non-magnetic field disturbance transverse relaxation rate R2 image; aligning the reconstructed quantitative susceptibility image with the prior quantitative susceptibility image to acquire the position of the ventral intermediate nucleus of the thalamus; and dividing the contour of the ventral intermediate nucleus of the thalamus on the diamagnetic susceptibility image based on the position of the ventral intermediate nucleus of the thalamus.

[0006] In an implementation of the first aspect, generating and reconstructing a quantitative magnetic susceptibility image based on the magnetic resonance multi-echo gradient echo data comprises the following steps:

[0007] performing phase unwrapping on the phase signal of the magnetic resonance multi-echo gradient echo data based on a Laplace operator;

[0008] The amplitude images corresponding to different echo signals in the magnetic resonance multi-echo gradient echo data are squared and merged, and the merged amplitude images are used to generate a brain mask based on the BET function using FSL; wherein the squared sum merging refers to squaring the amplitude image corresponding to each echo signal and then summing them;

[0009] The background field is removed from the phase signal after phase unwrapping using the VSHARP method.

[0010] The phase signal after background field removal is subjected to dipole inversion by STAR-QSM to obtain the reconstructed quantitative magnetic susceptibility image.

[0011] In an implementation of the first aspect, acquiring a paramagnetic susceptibility image and a diamagnetic susceptibility image based on the magnetic resonance multi-echo gradient echo data and the non-magnetic field disturbance transverse relaxation rate R2 image comprises the following steps:

[0012] Set the gradient echo signal of the jth echo Where M0 represents the amplitude signal when the echo time is equal to zero, a represents the amplitude attenuation kernel, φ res represents the residual phase not affected by the echo time, γ represents the gyromagnetic ratio, D represents the dipole nucleus in the acquisition direction, and χ para represents the paramagnetic susceptibility image, χ dia represents the reverse magnetic susceptibility image, B0 represents the magnetic induction intensity, TE j represents the echo time of the jth gradient echo, R2 represents the transverse relaxation decay rate of the non-magnetic field disturbance, 2πf bg TE j Represents the background field phase signal;

[0013] The paramagnetic susceptibility image and the diamagnetic susceptibility image are solved based on the objective function, and the objective function is:

[0014]

[0015] Where H is the total number of head rotation directions, N is the total number of echoes per scan, represents the unwrapped phase signal of the jth gradient echo time of the hth head direction scan, f bg,h represents the background field signal of the h-th head direction scan, χ para represents the paramagnetic susceptibility image, χ dia represents the reverse magnetic susceptibility image, represents the transverse relaxation decay rate of the magnetic field disturbance, and λ1 represents the regularization term weight of the first term in the solution formula.

[0016] In an implementation of the first aspect, based on the position of the ventral intermediate nucleus of the thalamus, dividing the contour of the ventral intermediate nucleus of the thalamus in the reverse magnetic susceptibility image comprises the following steps:

[0017] Based on the position of the ventral intermediate nucleus of the thalamus, extracting a region of interest including the ventral intermediate nucleus of the thalamus in the reverse magnetic susceptibility image;

[0018] Dividing the region of interest based on a k-means clustering algorithm to obtain the thalamic ventral intermediate nucleus region and the non-thalamic ventral intermediate nucleus region;

[0019] After morphological filtering is performed on the ventral intermediate nucleus region of the thalamus, the outline of the ventral intermediate nucleus of the thalamus is drawn.

[0020] In a second aspect, the present invention provides a thalamic ventral intermediate nucleus localization system, the system comprising an acquisition module, a generation module, a calculation module, a registration module and a localization module;

[0021] The acquisition module is used to acquire brain magnetic resonance multi-echo gradient echo data and non-magnetic field disturbance transverse relaxation rate R2 images;

[0022] The generating module is used to generate and reconstruct a quantitative magnetic susceptibility image based on the magnetic resonance multi-echo gradient echo data;

[0023] The calculation module is used to obtain a paramagnetic susceptibility image and a diamagnetic susceptibility image based on the magnetic resonance multi-echo gradient echo data and the non-magnetic field disturbance transverse relaxation rate R2 image;

[0024] The registration module is used to register the reconstructed quantitative magnetic susceptibility image with the prior quantitative magnetic susceptibility image to obtain the position of the ventral intermediate nucleus of the thalamus;

[0025] The positioning module is used to divide the contour of the ventral intermediate nucleus of the thalamus in the reverse magnetic susceptibility image based on the position of the ventral intermediate nucleus of the thalamus.

[0026] In an implementation of the second aspect, generating and reconstructing a quantitative magnetic susceptibility image based on the magnetic resonance multi-echo gradient echo data comprises the following steps:

[0027] performing phase unwrapping on the phase signal of the magnetic resonance multi-echo gradient echo data based on a Laplace operator;

[0028] The amplitude images corresponding to different echo signals in the magnetic resonance multi-echo gradient echo data are squared and merged, and the merged amplitude images are used to generate a brain mask based on the BET function using FSL; wherein the squared sum merging refers to squaring the amplitude image corresponding to each echo signal and then summing them;

[0029] The background field is removed from the phase signal after phase unwrapping using the VSHARP method.

[0030] The phase signal after background field removal is subjected to dipole inversion by STAR-QSM to obtain the reconstructed quantitative magnetic susceptibility image.

[0031] In an implementation of the second aspect, acquiring a paramagnetic susceptibility image and a diamagnetic susceptibility image based on the magnetic resonance multi-echo gradient echo data and the non-magnetic field disturbance transverse relaxation rate R2 image comprises the following steps:

[0032] Set the gradient echo signal of the jth echo Where M0 represents the return

[0033] The amplitude signal when the wave time is equal to zero, a represents the amplitude attenuation kernel, φ res represents the residual phase not affected by the echo time, γ represents the gyromagnetic ratio, D represents the dipole nucleus in the acquisition direction, and X para represents the paramagnetic susceptibility image, X dia represents the reverse magnetic susceptibility image, B0 represents the magnetic induction intensity, TE j represents the echo time of the jth gradient echo, R2 represents the transverse relaxation decay rate of the non-magnetic field disturbance, 2πf bg TE j Represents the background field phase signal;

[0034] The paramagnetic susceptibility image and the diamagnetic susceptibility image are solved based on the objective function, and the objective function is:

[0035]

[0036] Where H is the total number of head rotation directions, N is the total number of echoes per scan, represents the unwrapped phase signal of the jth gradient echo time of the hth head direction scan, f bg,h represents the background field signal of the h-th head direction scan, χ para represents the paramagnetic susceptibility image, χ dia represents the reverse magnetic susceptibility image, represents the transverse relaxation decay rate of the magnetic field disturbance, and λ1 represents the regularization term weight of the first term in the solution formula.

[0037] In an implementation of the second aspect, based on the position of the ventral intermediate nucleus of the thalamus, dividing the contour of the ventral intermediate nucleus of the thalamus in the reverse magnetic susceptibility image comprises the following steps:

[0038] Based on the position of the ventral intermediate nucleus of the thalamus, extracting a region of interest including the ventral intermediate nucleus of the thalamus in the reverse magnetic susceptibility image;

[0039] Dividing the region of interest based on a k-means clustering algorithm to obtain the thalamic ventral intermediate nucleus region and the non-thalamic ventral intermediate nucleus region;

[0040] After morphological filtering is performed on the ventral intermediate nucleus region of the thalamus, the outline of the ventral intermediate nucleus of the thalamus is drawn.

[0041] In a third aspect, the present invention provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for locating the ventral intermediate nucleus of the thalamus.

[0042] In a fourth aspect, the present invention provides an electronic device, comprising: a processor and a memory;

[0043] The memory is used to store computer programs;

[0044] The processor is used to execute the computer program stored in the memory so that the electronic device executes the above-mentioned method for locating the ventral intermediate nucleus of the thalamus.

[0045] As described above, the ventral intermediate nucleus of the thalamus positioning method, system, medium, and electronic device of the present invention have the following beneficial effects:

[0046] (1) Subvoxel-level quantitative magnetic susceptibility imaging technology can achieve ultra-fine localization of the Vim nucleus, which is significantly better than the spatial resolution limitations of conventional MRI and helps to improve the accuracy of surgical target positioning;

[0047] (2) By independently solving the paramagnetic and diamagnetic susceptibility images, the positioning ambiguity problem caused by the confusion of paramagnetic and diamagnetic materials in traditional QSM technology is solved, ensuring the specificity and accuracy of the positioning of the Vim nucleus, which is conducive to more accurately revealing the microstructure and organizational characteristics of the Vim nucleus;

[0048] (3) The use of automated processes greatly reduces the impact of manual operations and subjective judgment, improves positioning efficiency and accuracy, and has important clinical practice value. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 Shown is a schematic diagram of the location of the ventral intermediate nucleus of the thalamus in an embodiment in a T1-weighted image and a quantitative magnetic susceptibility image;

[0050] Figure 2It is a flow chart of a method for locating the ventral intermediate nucleus of the thalamus according to an embodiment of the present invention;

[0051] Figure 3 A schematic diagram showing a model of subvoxel quantitative susceptibility imaging in one embodiment of the present invention;

[0052] Figure 4 It is a schematic diagram showing a paramagnetic susceptibility image and a diamagnetic susceptibility image in subvoxel quantitative susceptibility imaging of the present invention in one embodiment;

[0053] Figure 5 It is a schematic diagram showing the position of the ventral intermediate nucleus of the thalamus in one embodiment of the ventral intermediate nucleus of the thalamus positioning method of the present invention;

[0054] Figure 6 It is a schematic structural diagram of the thalamic ventral intermediate nucleus localization system in one embodiment of the present invention;

[0055] Figure 7 It is a schematic structural diagram of an electronic device of the present invention in one embodiment. DETAILED DESCRIPTION

[0056] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0057] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0058] The technical solutions in the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0059] like Figure 2 As shown, in one embodiment, the method for locating the ventral intermediate nucleus of the thalamus of the present invention includes steps S1 to S5.

[0060] Step S1, acquiring brain magnetic resonance multi-echo gradient echo data and non-magnetic field disturbance transverse relaxation rate R2 images.

[0061] Specifically, the magnetic resonance multi-echo gradient echo (GRE) data includes an amplitude signal and a phase signal. The GRE data is obtained by collecting multiple brain direction signals and establishing a direct and inverse magnetic signal equation for each collection. The transverse relaxation decay rate of the magnetic field disturbance The image is obtained by collecting a multi-echo spin echo (MSE) image and fitting it. The fitting process is as follows: Wherein M0 represents the amplitude signal when the echo time of the gradient echo signal is equal to zero under theoretical conditions, and TE represents the echo time.

[0062] Step S2: generating and reconstructing a quantitative magnetic susceptibility image based on the magnetic resonance multi-echo gradient echo data.

[0063] Specifically, generating and reconstructing a quantitative magnetic susceptibility image based on the magnetic resonance multi-echo gradient echo data comprises the following steps:

[0064] 21) Performing phase unwrapping on the phase signal of the magnetic resonance multi-echo gradient echo data based on a Laplace operator.

[0065] 22) Square and merge the amplitude images corresponding to different echo signals in the magnetic resonance multi-echo gradient echo data, and generate a brain mask based on the merged amplitude image using the BET function of FSL; wherein the square and merge refers to square and sum the amplitude images corresponding to each echo signal.

[0066] 23) The background field of the phase signal after phase unwrapping is removed by using variable kernels sophisticated harmonic artifact reduction for phase data (VSHARP).

[0067] 24) Performing dipole inversion on the phase signal after removing the background field by using a streaking artifact reduction for quantitative susceptibility mapping (STAR-QSM) reconstruction algorithm to obtain the reconstructed quantitative susceptibility image.

[0068] Step S3, acquiring a paramagnetic susceptibility image and a diamagnetic susceptibility image based on the magnetic resonance multi-echo gradient echo data and the non-magnetic field disturbance transverse relaxation rate R2 image.

[0069] Specifically, since both paramagnetic and diamagnetic materials affect the magnetic field, the GRE amplitude signal produces an additional echo time (TE j ) attenuation. The phase signals generated by these two materials with opposite magnetic properties partially or completely cancel each other out, thus affecting the overall acquired GRE phase signal. In addition, considering the tissue intrinsic attenuation rate R2 that is not disturbed by the magnetic field and the background field phase signal (2πf bg TE j ), under the condition of given magnetic induction intensity (B0), the total signal formula S is expressed as:

[0070]

[0071] Where M0 represents the amplitude signal when the echo time is equal to zero, a represents the amplitude attenuation kernel, φ res represents the residual phase not affected by the echo time, γ represents the gyromagnetic ratio, D represents the dipole nucleus in the acquisition direction, and χ para represents the paramagnetic susceptibility image, χ dia represents the reverse magnetic susceptibility image, B0 represents the magnetic induction intensity, TE j represents the echo time, R2 represents the transverse relaxation decay rate without magnetic field disturbance, 2πf bg TE j Represents the background field phase signal.

[0072] Let a be initialized to a preset value, such as 323.5Hz / ppm, and the background field phase, Substituting R2 into the model to solve the least squares optimization problem, the initial paramagnetic susceptibility image and diamagnetic susceptibility image can be obtained. The paramagnetic susceptibility image and diamagnetic susceptibility image are calculated by alternating iterations. When convergence is reached, the iteration is stopped. The result obtained at this time is a high-quality multi-directional paramagnetic susceptibility image and diamagnetic susceptibility image. The paramagnetic susceptibility image and diamagnetic susceptibility image are solved based on the following objective function.

[0073]

[0074] Where H is the total number of head rotation directions, N is the total number of echoes per scan, represents the unwrapped phase signal of the jth gradient echo time of the hth head direction scan, f bg,h represents the background field signal of the h-th head direction scan, X para represents the paramagnetic susceptibility image, χ dia represents the reverse magnetic susceptibility image, represents the transverse relaxation decay rate of the magnetic field disturbance, and λ1 represents the regularization term weight of the first term in the solution formula.

[0075] like Figure 3The figure shows a schematic diagram of subvoxel quantitative magnetic susceptibility imaging. As can be seen from the figure, compared with the traditional quantitative QSM, the subvoxel quantitative magnetic susceptibility imaging of the present invention clearly distinguishes between the paramagnetic magnetic susceptibility image and the diamagnetic magnetic susceptibility image. Figure 4 The figure shows a comparison diagram of paramagnetic susceptibility images and diamagnetic susceptibility images in subvoxel quantitative susceptibility imaging, in which paramagnetic susceptibility images, diamagnetic susceptibility images and quantitative susceptibility images in transverse, sagittal and coronal planes are shown.

[0076] Step S4: registering the reconstructed quantitative susceptibility image with the prior quantitative susceptibility image to obtain the position of the ventral intermediate nucleus of the thalamus.

[0077] Specifically, the label information of the ventral intermediate nucleus of the thalamus in the prior quantitative susceptibility image is directly mapped to the reconstructed quantitative susceptibility image, ensuring that the positions of each ventral intermediate nucleus of the thalamus marked in the prior quantitative susceptibility image accurately correspond to the corresponding positions in the reconstructed quantitative susceptibility image, thereby identifying the location of the ventral intermediate nucleus of the thalamus.

[0078] Step S5: based on the position of the ventral intermediate nucleus of the thalamus, dividing the contour of the ventral intermediate nucleus of the thalamus in the reverse magnetic susceptibility image.

[0079] Specifically, firstly, based on the location of the ventral intermediate nucleus of the thalamus, a region of interest (ROI) containing the ventral intermediate nucleus of the thalamus is extracted from the diamagnetic susceptibility image, wherein it is necessary to ensure that the region of interest only covers the ventral intermediate nucleus of the thalamus and its surrounding adjacent structures that may be confused with the boundary of the ventral intermediate nucleus of the thalamus, thereby excluding irrelevant areas to reduce computational complexity and potential mis-segmentation.

[0080] Next, the region of interest is divided based on the k-means clustering algorithm to obtain the ventral intermediate nucleus of the thalamus region and the non-ventral intermediate nucleus of the thalamus region. Among them, the number of clusters k is fixed to 2, one cluster represents the ventral intermediate nucleus of the thalamus region, and the other cluster represents the non-ventral intermediate nucleus of the thalamus region. The diamagnetic susceptibility values ​​of k pixels in the region of interest are randomly selected as the initial centroid. For each pixel in the region of interest, its distance from the current two centroids is calculated, and it is assigned to the cluster to which the nearest centroid belongs. According to the average value (or weighted average value) of the diamagnetic susceptibility values ​​of all pixels in each cluster, the centroid position of each cluster is recalculated. Repeat the above steps and continue to iterate until the preset stop criterion is reached. Each iteration adjusts the pixel allocation and centroid position to gradually optimize the clustering results. Based on the clustering results, the region of interest is divided into the ventral intermediate nucleus of the thalamus region and the non-ventral intermediate nucleus of the thalamus region.

[0081] Then, the ventral intermediate nucleus of the thalamus region is subjected to morphological filtering (such as dilation, erosion, opening operation, closing operation, etc.), and the aforementioned ventral intermediate nucleus of the thalamus region division result is refined to eliminate small noise patches, fill small holes in the segmentation boundary, and smooth the edge of the ventral intermediate nucleus of the thalamus, thereby improving the robustness and visual effect of the ventral intermediate nucleus of the thalamus region segmentation.

[0082] Finally, the outline of the ventral intermediate nucleus of the thalamus is drawn along the boundary of the ventral intermediate nucleus of the thalamus.

[0083] like Figure 5 The figure shows the schematic diagram of the positioning effect of the ventral intermediate nucleus of the thalamus in the ventral intermediate nucleus positioning method of the present invention. As can be seen from the figure, the present invention can achieve ultra-fine positioning of the ventral intermediate nucleus of the thalamus, which is significantly better than the limitation of conventional MRI in spatial resolution, and helps to improve the accuracy of surgical target positioning.

[0084] The protection scope of the method for locating the ventral intermediate nucleus of the thalamus described in the embodiment of the present invention is not limited to the execution order of the steps listed in this embodiment. All solutions implemented by adding, reducing or replacing steps in the prior art based on the principles of the present invention are included in the protection scope of the present invention.

[0085] An embodiment of the present invention also provides a thalamic ventral intermediate nucleus locating system, which can implement the thalamic ventral intermediate nucleus locating method described in the present invention. However, the implementation device of the thalamic ventral intermediate nucleus locating system described in the present invention includes but is not limited to the structure of the thalamic ventral intermediate nucleus locating system listed in this embodiment. All structural deformations and replacements of the prior art made according to the principles of the present invention are included in the protection scope of the present invention.

[0086] like Figure 6 As shown, in one embodiment, the ventral intermediate nucleus of thalamus positioning system provided by the present invention includes an acquisition module 61, a generation module 62, a calculation module 63, a registration module 64 and a positioning module 65.

[0087] The acquisition module 61 is used to acquire brain magnetic resonance multi-echo gradient echo data and non-magnetic field disturbance transverse relaxation rate R2 images.

[0088] The generating module 62 is connected to the acquiring module 61 and is used to generate and reconstruct a quantitative magnetic susceptibility image based on the magnetic resonance multi-echo gradient echo data.

[0089] The calculation module 63 is connected to the acquisition module 61, and is used to acquire a paramagnetic susceptibility image and a diamagnetic susceptibility image based on the magnetic resonance multi-echo gradient echo data and the non-magnetic field disturbance transverse relaxation rate R2 image.

[0090] The registration module 64 is connected to the generation module 62 and is used to register the reconstructed quantitative magnetic susceptibility image with the prior quantitative magnetic susceptibility image to obtain the position of the ventral intermediate nucleus of the thalamus.

[0091] The positioning module 65 is connected to the calculation module 63 and the registration module 64, and is used to divide the contour of the ventral intermediate nucleus of the thalamus in the reverse magnetic susceptibility image based on the position of the ventral intermediate nucleus of the thalamus.

[0092] Among them, the structures and principles of the acquisition module 61, the generation module 62, the calculation module 63, the registration module 64 and the positioning module 65 correspond one to one with the above-mentioned ventral intermediate nucleus of the thalamus positioning method, so they are not repeated here.

[0093] In the several embodiments provided by the present invention, it should be understood that the disclosed system, device or method can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of modules / units is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules or units can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules or units, which can be electrical, mechanical or other forms.

[0094] The modules / units described as separate components may or may not be physically separated, and the components displayed as modules / units may or may not be physical modules, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules / units may be selected according to actual needs to achieve the purpose of the embodiments of the present invention. For example, the functional modules / units in the various embodiments of the present invention may be integrated into one processing module, or each module / unit may exist physically separately, or two or more modules / units may be integrated into one module / unit.

[0095] Those of ordinary skill in the art should further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0096] The embodiment of the present invention also provides a computer-readable storage medium. A person of ordinary skill in the art can understand that all or part of the steps in the method for locating the ventral intermediate nucleus of the thalamus in the above embodiment can be completed by instructing a processor through a program, and the program can be stored in a computer-readable storage medium, and the storage medium is a non-transitory medium, such as a random access memory, a read-only memory, a flash memory, a hard disk, a solid-state hard disk, a magnetic tape, a floppy disk, an optical disc, and any combination thereof. The above storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more available media. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a digital video disc (DVD)), or a semiconductor medium (e.g., a solid-state disk (SSD)), etc.

[0097] An embodiment of the present invention further provides an electronic device, which includes a processor and a memory.

[0098] The memory is used to store computer programs.

[0099] The memory includes: ROM, RAM, disk, USB flash drive, memory card or CD and other media that can store program codes.

[0100] The processor is connected to the memory and is used to execute the computer program stored in the memory so that the electronic device executes the above-mentioned method for locating the ventral intermediate nucleus of the thalamus.

[0101] Preferably, the processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0102] like Figure 7As shown, the electronic device of the present invention is in the form of a general computing device. The components of the electronic device may include but are not limited to: one or more processors or processing units 71, a memory 72, and a bus 73 connecting different system components (including the memory 72 and the processing unit 71).

[0103] Bus 73 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0104] Electronic devices typically include a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device, including volatile and non-volatile media, removable and non-removable media.

[0105] The memory 72 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 721 and / or cache memory 722. The electronic device may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 723 may be used to read and write non-removable, non-volatile magnetic media ( Figure 7 not shown, usually called a "hard drive"). Although Figure 7 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 73 via one or more data medium interfaces. The memory 72 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0106] A program / utility 724 having a set (at least one) of program modules 7241 may be stored, for example, in the memory 72, such program modules 7241 including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 7241 generally perform the functions and / or methods of the embodiments described herein.

[0107] The electronic device may also communicate with one or more external devices (e.g., keyboards, pointing devices, displays, etc.), one or more devices that enable a user to interact with the electronic device, and / or any device that enables the electronic device to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via input / output (I / O) interface 74. Furthermore, the electronic device may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via network adapter 75. Figure 7 As shown, the network adapter 75 communicates with other modules of the electronic device via the bus 73. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0108] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by a person of ordinary skill in the art without departing from the spirit and technical concept disclosed by the present invention shall still be covered by the claims of the present invention.

Claims

1. A method for locating the ventral intermediate nucleus of the thalamus, characterized in that: The method comprises the following steps: Acquire brain magnetic resonance multi-echo gradient echo data and non-magnetic field perturbation transverse relaxation rate R2 images; generating a reconstructed quantitative magnetic susceptibility image based on the magnetic resonance multi-echo gradient echo data; Acquire a paramagnetic susceptibility image and a diamagnetic susceptibility image based on the magnetic resonance multi-echo gradient echo data and the non-magnetic field disturbance transverse relaxation rate R2 image; Registering the reconstructed quantitative magnetic susceptibility image with the prior quantitative magnetic susceptibility image to obtain the position of the ventral intermediate nucleus of the thalamus; Based on the position of the ventral intermediate nucleus of the thalamus, dividing the contour of the ventral intermediate nucleus of the thalamus on the reverse magnetic susceptibility image; performing phase unwrapping on the phase signal of the magnetic resonance multi-echo gradient echo data based on a Laplace operator; The amplitude images corresponding to different echo signals in the magnetic resonance multi-echo gradient echo data are squared and merged, and the merged amplitude images are used to generate a brain mask based on the BET function using FSL; wherein the squared sum merging refers to squaring the amplitude image corresponding to each echo signal and then summing them; The background field is removed from the phase signal after phase unwrapping using the VSHARP method. Performing dipole inversion on the phase signal after removing the background field by STAR-QSM to obtain the reconstructed quantitative magnetic susceptibility image; Based on the magnetic resonance multi-echo gradient echo data and the non-magnetic field disturbance transverse relaxation rate R2 image, acquiring a paramagnetic susceptibility image and a diamagnetic susceptibility image comprises the following steps: Set the gradient echo signal of the jth echo Where M0 represents the amplitude signal when the echo time is equal to zero, a represents the amplitude attenuation kernel, φ res represents the residual phase not affected by the echo time, γ represents the gyromagnetic ratio, D represents the dipole nucleus in the acquisition direction, and χ para represents the paramagnetic susceptibility image, χ dia represents the reverse magnetic susceptibility image, B0 represents the magnetic induction intensity, TE j represents the echo time of the jth gradient echo, R2 represents the transverse relaxation decay rate of the non-magnetic field disturbance, 2πf bg TE j Represents the background field phase signal; The paramagnetic susceptibility image and the diamagnetic susceptibility image are solved based on the objective function, and the objective function is: Where H is the total number of head rotation directions, N is the total number of echoes per scan, represents the unwrapped phase signal of the jth gradient echo time of the hth head direction scan, f bg,h represents the background field signal of the h-th head direction scan, χ para represents the paramagnetic susceptibility image, χ dia represents the reverse magnetic susceptibility image, represents the transverse relaxation decay rate of the magnetic field disturbance, and λ1 represents the regularization term weight of the first term in the solution formula.

2. The method for locating the ventral intermediate nucleus of the thalamus according to claim 1, characterized in that: Based on the position of the ventral intermediate nucleus of the thalamus, dividing the contour of the ventral intermediate nucleus of the thalamus on the reverse magnetic susceptibility image comprises the following steps: Based on the position of the ventral intermediate nucleus of the thalamus, extracting a region of interest including the ventral intermediate nucleus of the thalamus in the reverse magnetic susceptibility image; Dividing the region of interest based on a k-means clustering algorithm to obtain the thalamic ventral intermediate nucleus region and the non-thalamic ventral intermediate nucleus region; After morphological filtering is performed on the ventral intermediate nucleus region of the thalamus, the outline of the ventral intermediate nucleus of the thalamus is drawn.

3. A thalamic ventral intermediate nucleus positioning system, characterized in that: The system includes an acquisition module, a generation module, a calculation module, a registration module and a positioning module; The acquisition module is used to acquire brain magnetic resonance multi-echo gradient echo data and non-magnetic field disturbance transverse relaxation rate R2 images; The generating module is used to generate and reconstruct a quantitative magnetic susceptibility image based on the magnetic resonance multi-echo gradient echo data; The calculation module is used to obtain a paramagnetic susceptibility image and a diamagnetic susceptibility image based on the magnetic resonance multi-echo gradient echo data and the non-magnetic field disturbance transverse relaxation rate R2 image; The registration module is used to register the reconstructed quantitative magnetic susceptibility image with the prior quantitative magnetic susceptibility image to obtain the position of the ventral intermediate nucleus of the thalamus; The positioning module is used to divide the contour of the ventral intermediate nucleus of the thalamus on the reverse magnetic susceptibility image based on the position of the ventral intermediate nucleus of the thalamus; performing phase unwrapping on the phase signal of the magnetic resonance multi-echo gradient echo data based on a Laplace operator; The amplitude images corresponding to different echo signals in the magnetic resonance multi-echo gradient echo data are squared and merged, and the merged amplitude images are used to generate a brain mask based on the BET function using FSL; wherein the squared sum merging refers to squaring the amplitude image corresponding to each echo signal and then summing them; The background field is removed from the phase signal after phase unwrapping using the VSHARP method. Performing dipole inversion on the phase signal after removing the background field by STAR-QSM to obtain the reconstructed quantitative magnetic susceptibility image; Based on the magnetic resonance multi-echo gradient echo data and the non-magnetic field disturbance transverse relaxation rate R2 image, acquiring a paramagnetic susceptibility image and a diamagnetic susceptibility image comprises the following steps: Set the gradient echo signal of the jth echo Where M0 represents the amplitude signal when the echo time is equal to zero, a represents the amplitude attenuation kernel, φ res represents the residual phase not affected by the echo time, γ represents the gyromagnetic ratio, D represents the dipole nucleus in the acquisition direction, and χ para represents the paramagnetic susceptibility image, χ dia represents the reverse magnetic susceptibility image, B0 represents the magnetic induction intensity, TE j represents the echo time of the jth gradient echo, R2 represents the transverse relaxation decay rate of the non-magnetic field disturbance, 2πf bg TE j Represents the background field phase signal; The paramagnetic susceptibility image and the diamagnetic susceptibility image are solved based on the objective function, and the objective function is: Where H is the total number of head rotation directions, N is the total number of echoes per scan, represents the unwrapped phase signal of the jth gradient echo time of the hth head direction scan, f bg,h represents the background field signal of the h-th head direction scan, χ para represents the paramagnetic susceptibility image, χ dia represents the reverse magnetic susceptibility image, represents the transverse relaxation decay rate of the magnetic field disturbance, and λ1 represents the regularization term weight of the first term in the solution formula.

4. The thalamic ventral intermediate nucleus positioning system according to claim 3, characterized in that: Based on the position of the ventral intermediate nucleus of the thalamus, dividing the contour of the ventral intermediate nucleus of the thalamus on the reverse magnetic susceptibility image comprises the following steps: Based on the position of the ventral intermediate nucleus of the thalamus, extracting a region of interest including the ventral intermediate nucleus of the thalamus in the reverse magnetic susceptibility image; Dividing the region of interest based on a k-means clustering algorithm to obtain the thalamic ventral intermediate nucleus region and the non-thalamic ventral intermediate nucleus region; After morphological filtering is performed on the ventral intermediate nucleus region of the thalamus, the outline of the ventral intermediate nucleus of the thalamus is drawn.

5. A storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for locating the ventral intermediate nucleus of the thalamus according to any one of claims 1 to 2 is implemented.

6. An electronic device, characterized in that: include: Processor and memory; The memory is used to store computer programs; The processor is used to execute the computer program stored in the memory, so that the electronic device executes the method for locating the ventral intermediate nucleus of the thalamus according to any one of claims 1 to 2.

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