Method, device, system and medium for determining stimulation targets based on brain function maps

Abstract

The embodiments of the present invention disclose a method, device, system and medium for determining stimulation targets based on a brain function map, comprising: acquiring a brain reconstructed image, aligning the brain reconstructed image with a standard brain function map to obtain a target brain function area image; performing three-dimensional reconstruction based on the target brain function area image to obtain a three-dimensional brain function area image; determining a target stimulation area according to the three-dimensional brain function area image, and determining candidate stimulation targets for the target stimulation area based on target setting parameters; adjusting the candidate stimulation targets based on difference verification parameters to obtain a target stimulation target for the target stimulation area, and displaying the target stimulation target. By determining the candidate stimulation targets in the brain reconstructed image based on the standard brain function map and then adjusting the target stimulation target, the setting of the stimulation target is more accurate.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of computer technology, and in particular to a method, device, system and medium for determining stimulation targets based on brain function maps. Background Art

[0002] Image-guided transcranial magnetic stimulation (TMS) using magnetic resonance imaging (MRI) has been widely used in clinical and scientific research. However, structural MRI images lack functional information, and researchers often rely on anatomical experience to determine the location of functional brain regions for stimulation and then set stimulation targets based on this judgment. This method of setting stimulation targets can introduce significant human error. Localizing stimulation areas using functional MRI requires complex experimental design and data processing, making it impractical for widespread clinical and scientific application. How to quickly and accurately set stimulation targets is a pressing technical challenge. Summary of the Invention

[0003] The embodiments of the present invention provide a method, device, system and medium for determining stimulation targets based on brain function maps, so as to achieve rapid and accurate setting of stimulation targets.

[0004] In a first aspect, an embodiment of the present invention provides a method for determining stimulation targets based on brain function maps, comprising:

[0005] Obtaining a brain reconstruction image, registering the brain reconstruction image with a standard brain function atlas, and obtaining an image of the target brain functional area;

[0006] Perform three-dimensional reconstruction based on the target brain functional area image to obtain a three-dimensional brain functional area image;

[0007] Determine the target stimulation area based on the three-dimensional brain functional area image, and determine the candidate stimulation targets in the target stimulation area based on the target setting parameters;

[0008] The candidate stimulation targets are adjusted based on the difference verification parameters to obtain the target stimulation targets in the target stimulation area, and the target stimulation targets are displayed.

[0009] Optionally, the reconstructed brain image is registered with a standard brain function atlas to obtain an image of the target brain function area, including:

[0010] Register the reconstructed brain image to the standard space template and determine the registration transformation matrix;

[0011] Based on the registration transformation matrix, the standard brain function areas in the standard brain function atlas are registered to the coordinate system of the brain reconstructed image to obtain the target brain function area image.

[0012] Optionally, the target stimulation area is determined based on the three-dimensional brain functional area image, including:

[0013] The area corresponding to the stimulation functional area in the three-dimensional brain functional area image is used as the target stimulation area.

[0014] Optionally, the target setting parameters include target spacing, target row number, and target column number. Determining candidate stimulation targets in the target stimulation area based on the target setting parameters includes:

[0015] Determine the center position of the target stimulation area, set the targets outward based on the target spacing based on the center position, and obtain candidate stimulation targets that meet the number of target rows and target columns.

[0016] Optionally, the candidate stimulation targets are adjusted based on the difference verification parameters to obtain the target stimulation targets in the target stimulation area, including:

[0017] Determine the difference deviation corresponding to the difference verification parameter;

[0018] An adjustment direction is determined based on the difference deviation, and the candidate stimulation target is adjusted according to the adjustment direction to obtain a target stimulation target in the target stimulation area.

[0019] Optionally, also include:

[0020] Obtaining a sample brain reconstructed image, and determining a sample stimulation target based on a sample brain functional area image obtained by registering the sample brain reconstructed image with a standard brain functional atlas;

[0021] Determine the actual stimulation target information according to the motor evoked potential sampled after stimulating the sample stimulation target;

[0022] The difference verification parameters are determined based on the sample stimulation target information and the actual stimulation target information.

[0023] Optionally, the actual stimulation target information includes the actual stimulation target position and the actual stimulation target intensity. Determining the difference verification parameter based on the sample stimulation target information and the actual stimulation target information includes:

[0024] The target position difference is determined based on the actual stimulation target position and the center position of the stimulated brain functional area;

[0025] The target distribution difference is determined based on the number of actual stimulation targets whose actual stimulation target intensity is greater than the set intensity;

[0026] The difference validation parameters are determined based on the differences in target location and target distribution.

[0027] In a second aspect, an embodiment of the present invention further provides a device for determining stimulation targets based on a brain function map, comprising:

[0028] The brain function area registration module is used to obtain a brain reconstruction image, register the brain reconstruction image with a standard brain function atlas, and obtain a target brain function area image;

[0029] A three-dimensional reconstruction module is used to perform three-dimensional reconstruction based on the target brain functional area image to obtain a three-dimensional brain functional area image;

[0030] A candidate target determination module is used to determine the target stimulation area based on the three-dimensional brain functional area image and determine the candidate stimulation targets in the target stimulation area based on the target setting parameters;

[0031] The target target determination module is used to adjust the candidate stimulation targets based on the difference verification parameters, obtain the target stimulation targets in the target stimulation area, and display the target stimulation targets.

[0032] In a third aspect, an embodiment of the present invention further provides a device for determining stimulation targets based on a brain function map, the device comprising:

[0033] one or more processors;

[0034] a storage device for storing one or more programs;

[0035] a display for displaying images;

[0036] When one or more programs are executed by one or more processors, the one or more processors implement the method for determining stimulation targets based on brain function maps as provided in any embodiment of the present invention.

[0037] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, characterized in that when the program is executed by a processor, it implements a method for determining stimulation targets based on brain function maps as provided in any embodiment of the present invention.

[0038] The embodiment of the present invention obtains a brain reconstructed image, aligns the brain reconstructed image with a standard brain function map, and obtains a target brain function area image; performs three-dimensional reconstruction based on the target brain function area image to obtain a three-dimensional brain function area image; determines a target stimulation area according to the three-dimensional brain function area image, and determines candidate stimulation targets in the target stimulation area based on target setting parameters; adjusts the candidate stimulation targets based on difference verification parameters to obtain a target stimulation target in the target stimulation area, and displays the target stimulation target. By determining the candidate stimulation targets in the brain reconstructed image based on the standard brain function map and then adjusting them to obtain the target stimulation target, the setting of the stimulation target is more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1This is a flow chart of a method for determining stimulation targets based on brain function maps provided in Example 1 of the present invention;

[0040] Figure 2 This is a flow chart of a method for determining stimulation targets based on brain function maps provided in the second embodiment of the present invention;

[0041] Figure 3 This is a schematic structural diagram of a device for determining stimulation targets based on brain function maps provided in Example 3 of the present invention;

[0042] Figure 4 It is a structural diagram of a computer device provided in Example 4 of the present invention. DETAILED DESCRIPTION

[0043] The present invention will be further described in detail below with reference to the accompanying drawings and examples. It will be understood that the specific embodiments described herein are intended only to illustrate the present invention and are not intended to limit the present invention. It should also be noted that, for ease of description, the accompanying drawings only illustrate portions relevant to the present invention, not all structures.

[0044] Example 1

[0045] Figure 1 This is a flow chart of a method for determining a stimulation target based on a brain function map provided by the first embodiment of the present invention. This embodiment is applicable to situations where stimulation targets are located during transcranial magnetic stimulation. The method can be performed by a stimulation target determination device based on a brain function map. The stimulation target determination device based on a brain function map can be implemented in software and / or hardware. For example, the stimulation target determination device based on a brain function map can be configured in a computer device. Figure 1 As shown, the method includes:

[0046] S110 , obtaining a brain reconstruction image, registering the brain reconstruction image with a standard brain function atlas, and obtaining an image of a target brain function area.

[0047] In order to solve the technical problems that the existing technology relies on anatomical experience to determine the location of brain functional areas to be stimulated and the method of setting stimulation targets is subject to human errors, and that locating and stimulating brain functional areas through functional magnetic resonance imaging requires complex experimental design and data processing processes, which cannot be widely used. The embodiments of the present invention use brain function maps to assist in locating and outlining the stimulation brain functional areas, and automatically set stimulation targets based on the shapes of the outlined brain functional areas, thereby providing a low-cost and universal method for locating and outlining brain functional areas for TMS, reducing the human errors caused by the setting of TMS stimulation targets, and thus improving the TMS stimulation effect.

[0048] Among them, the standard brain function atlas can adopt but is not limited to the brain network group atlas released by the Institute of Automation of the Chinese Academy of Sciences in 2016. The brain network group atlas obtains 246 brain function divisions and connection relationships, which is 4-5 times more detailed than the traditional Brodmann atlas and has objective and accurate boundary positioning.

[0049] In this embodiment, the reconstructed brain image can be a reconstructed brain image of the stimulated subject, such as a magnetic resonance imaging (MRI) reconstructed image of the stimulated subject. Based on scanning principles, the image reconstructed from the scan data includes images of each scan layer. The reconstructed images of each layer can be processed as a reconstructed brain image to obtain an image of the target brain functional area at each layer, thereby reconstructing a three-dimensional brain functional area image with accurate brain functional area delineation.

[0050] It is understood that the purpose of registering the reconstructed brain image with the standard brain function image is to partition the reconstructed brain image into functional brain regions based on the standard functional brain regions in the standard functional brain image, thereby avoiding errors caused by artificial division of functional brain regions. The registration of the reconstructed brain image with the annotated brain function map can be accomplished using existing registration methods, which are not limited here.

[0051] In one embodiment, the brain reconstructed image and the standard brain function atlas are registered to obtain the target brain function area image, including: registering the brain reconstructed image to the standard space template and determining the registration transformation matrix; based on the registration transformation matrix, registering the standard brain function area in the standard brain function atlas to the coordinate system of the brain reconstructed image to obtain the target brain function area image. Optionally, the registration between images can be performed based on the standard brain function atlas. Specifically, the brain reconstructed image is registered to the MNI152 standard space template, and the registration transformation matrix M is saved at the same time, and then the inverse matrix M1 of the registration transformation matrix M is determined, and the inverse matrix M1 of the registration transformation matrix M is applied to register the standard brain function area in the standard brain function atlas to the coordinate system of the brain reconstructed image. The specific method for determining the registration transformation matrix and the inverse matrix can refer to the method for determining the transformation matrix and the inverse matrix in the prior art, and is not limited here.

[0052] When the reconstructed brain image is a multi-layer image, the corresponding registration operation is performed on each layer of the reconstructed brain image to obtain its corresponding target brain functional area image. In other words, when the reconstructed brain image is multiple, the corresponding target brain functional area images are also multiple.

[0053] S120 , performing three-dimensional reconstruction based on the target brain functional area image to obtain a three-dimensional brain functional area image.

[0054] After obtaining the target brain functional area image corresponding to each layer of the reconstructed brain image, a three-dimensional reconstruction is performed based on the target brain functional area images of each layer to obtain a three-dimensional brain functional area image. The method of three-dimensional reconstruction is not limited herein. After obtaining the three-dimensional brain functional area image, the three-dimensional brain functional area image can be displayed. It is understood that the three-dimensional brain functional area image is a three-dimensional brain image that has been divided into each brain functional area.

[0055] S130 , determining a target stimulation area according to the three-dimensional brain functional area image, and determining candidate stimulation targets in the target stimulation area based on target setting parameters.

[0056] In this embodiment, the target stimulation area may be an area determined based on the stimulation target. It may be determined based on user input. After the target stimulation area is determined, coordinate points within the target stimulation area are selected as candidate stimulation targets. For example, points within the target stimulation area may be randomly selected as candidate stimulation targets, or target parameters may be pre-set and candidate stimulation targets within the target stimulation area may be determined based on the pre-set target parameters.

[0057] Optionally, determining the target stimulation area based on the three-dimensional brain function area image includes: taking the area corresponding to the stimulation function area in the three-dimensional brain function area image as the target stimulation area. The three-dimensional brain function area includes brain function areas and their corresponding functions. Therefore, the area corresponding to the stimulation function in the three-dimensional brain function area can be used as the target stimulation area. The stimulation function area can be determined by the user through input. Exemplarily, assuming that the upper limb motor function needs to be stimulated, the stimulation function area is the upper limb motor function area, and the area corresponding to the upper limb motor function area in the three-dimensional brain function area image is used as the target stimulation area. The target stimulation area determined based on the three-dimensional brain function area image is more accurate.

[0058] In one embodiment of the present invention, the target setting parameters include target point spacing, target point row number and target point column number, and the candidate stimulation targets of the target stimulation area are determined based on the target point setting parameters, including: determining the center position of the target stimulation area, setting targets based on the target point spacing outward with the center position as the reference, and obtaining candidate stimulation targets that meet the target point row number and target point column number. Optionally, the user can pre-set the target point spacing, target point row number and target point column number as target setting parameters. After determining the target stimulation area, the candidate stimulation targets of the target point column number and target point row number are set based on the target point spacing. Among them, the target point spacing can be understood as the distance between adjacent target points, the target point row number can be understood as the total number of target rows, and the target point column number can be understood as the total number of target columns. The candidate stimulation targets can be set based on any point as the reference. In order to make the distribution of the targets more uniform, the targets can be set in sequence around the center position of the target stimulation area as the reference. The center area of ​​the target stimulation area can be selected manually or calculated by the coordinates of the target stimulation area, which is not limited here.

[0059] S140 , adjusting the candidate stimulation targets based on the difference verification parameters to obtain the target stimulation targets in the target stimulation area, and displaying the target stimulation targets.

[0060] It is understood that candidate stimulation targets are determined based on the target stimulation area obtained through registration. Therefore, when there is a deviation in the division of the target stimulation area, the setting of candidate stimulation targets will also be biased. On this basis, in order to make the target setting more accurate, the coordinates of the candidate stimulation targets can be adjusted to obtain the target stimulation targets for display.

[0061] In one embodiment, the difference verification parameters of the stimulation target determined by this embodiment can be obtained by using an individual difference verification method. When the target stimulation target is actually determined, the candidate stimulation targets are adjusted based on the predetermined difference verification parameters to obtain the target stimulation target.

[0062] The difference verification parameter may be the positional deviation between the candidate stimulation target and the target stimulation target. Adjusting the candidate stimulation target based on the difference verification parameter to obtain the target stimulation target in the target stimulation area includes: determining the difference deviation corresponding to the difference verification parameter; determining the adjustment orientation based on the difference deviation, and adjusting the candidate stimulation target according to the adjustment orientation to obtain the target stimulation target in the target stimulation area. Optionally, the difference verification parameter may include its corresponding positional deviation and quantity deviation. The adjustment orientation may be determined based on the positional deviation, and the candidate stimulation target may be adjusted accordingly to the adjustment orientation; and the candidate stimulation targets may be added or subtracted based on the quantity deviation to obtain the target stimulation target. The positional deviation may be the deviation between the position of the feature point of the candidate stimulation target and the position of the feature point of the target stimulation target. After determining the adjustment orientation, the feature points of the candidate stimulation target may be adjusted along the adjustment orientation so that the feature points of the candidate stimulation target and the feature points of the target stimulation target coincide. That is, all candidate stimulation targets are adjusted as a whole along the adjustment orientation based on the adjustment orientation to complete the position correction of the candidate stimulation targets. The feature point may be a center point, a point with maximum intensity, etc., which is not limited here.

[0063] In this embodiment, the difference verification parameters can be implemented through individual difference verification. Based on this, the method provided in the embodiment of the present invention also includes: obtaining a sample brain reconstructed image, determining a sample stimulation target based on a sample brain function area image obtained by aligning the sample brain reconstructed image with a standard brain function atlas; determining actual stimulation target information based on the motor evoked potential sampled after stimulating the sample stimulation target; and determining the difference verification parameters based on the sample stimulation target information and the actual stimulation target information. A certain number of sample brain reconstructed images can be obtained, and the sample stimulation target corresponding to each sample brain reconstructed image can be determined using the above-mentioned stimulation target determination method. Stimulation is performed based on the sample stimulation target, and the difference verification parameters are determined based on the stimulation response. Specifically, a sample brain reconstructed image is obtained, and the sample brain reconstructed image is aligned with a standard brain function atlas to obtain a sample brain function area image; three-dimensional reconstruction is performed based on the sample brain function area image to obtain a sample three-dimensional brain function area image; a sample stimulation area is determined based on the sample three-dimensional brain function area image, and the sample stimulation target of the sample stimulation area is determined based on the target setting parameters. More specific implementation methods can be referred to the above embodiments and will not be repeated here.

[0064] Alternatively, the right upper limb motor function area can be used as the stimulation function area, and the difference verification parameters can be determined based on the motor evoked potential generated by stimulating the function area. 10 healthy adults can be recruited as experimental samples. First, MRI image data acquisition is performed on the sample to generate a sample brain reconstruction image. Then, based on the sample brain reconstruction image and the standard brain function atlas, the brain function areas in the sample brain reconstruction image are outlined to obtain the sample brain function area image. Based on the sample brain function area image, a sample three-dimensional brain function area image is reconstructed. The right upper limb motor function area in the sample three-dimensional brain function area image is used as the sample stimulation area, and then the sample stimulation target is determined based on the stimulation target setting method of the brain function area. Specifically, the above-mentioned target setting method is used to set stimulation targets in the left and right upper limb motor function areas A4ul_l and A4ul_r of each sample, with a target spacing of 2mm. The matrix size completely covers the stimulation brain function area, and ensures that the outermost stimulation target of the target matrix is ​​greater than 4mm away from the brain function area. After determining the sample stimulation target, each sample is stimulated based on the sample stimulation target, the motor evoked potential generated by the target stimulation is collected, and the actual stimulation target information is determined based on the motor evoked potential; the difference verification parameters are determined based on the sample stimulation target information and the actual stimulation target information.

[0065] When stimulating the sample stimulation targets, the EMG electrodes can be fixed to the first dorsal interosseous muscles of the left and right hands. To ensure target positioning accuracy, the subject's head is fixed with a bracket. After positioning the magnetic stimulation coil to the stimulation target using a robotic arm, the robotic arm is fine-tuned to ensure target positioning accuracy within 1 mm. Using 120% of the resting motor threshold, 10 TMS stimulations are administered to each stimulation target in sequence. The intensity S and probability P of the motor evoked potential are recorded. The intensity probability Ps is defined as P*S. The difference verification parameter is calculated based on the collected motor evoked potential information.

[0066] In one embodiment of the present invention, the actual stimulation target information includes the actual stimulation target position and the actual stimulation target intensity, and the difference verification parameters are determined based on the sample stimulation target information and the actual stimulation target information, including: determining the target position difference according to the actual stimulation target position and the center position of the stimulated brain functional area; determining the target distribution difference according to the number of actual stimulation targets whose actual stimulation target intensity is greater than the set intensity; and determining the difference verification parameters according to the target position difference and the target distribution difference.

[0067] Optionally, the following formula (1) can be used to respectively calculate the mean and variance of the distance between the target coordinates of the maximum MEP intensity probability Ps obtained from the left and right upper limb motor functional areas A4ul_l and A4ul_r of the subject and the center of the brain functional area, and obtain the individual differences in the maximum MEP position coordinates as the target position differences.

[0068]

[0069] Among them, for each subject i, the target position coordinate x i ,y i , z i , satisfying Ps(x i ,y i ,z i )=max(Ps).u x ,u y ,u z , are the center coordinates of the brain functional area.

[0070] The number of target points N with MEP intensity probability Ps>0.5*max(Ps) obtained in the motor function areas A4ul_l and A4ul_r of the left and right upper limbs of subject i can be counted by the following formula (2): i The variance of was used to obtain the individual differences in the MEP half-wave intensity distribution range as the target distribution differences.

[0071]

[0072] According to formula (3), the number of target points with MEP intensity probability Ps>0.5*max(Ps) obtained from the motor functional areas A4ul_l and A4ul_r of the left and right upper limbs of the subject, located outside the brain functional area outlined by the subject i, is counted. mis The mean of is also used as the target distribution difference.

[0073]

[0074] The individual differences in the coordinates of the maximum MEP position, the individual differences in the distribution range of the MEP half-wave intensity, and the target points, and the number N of target points outside the brain functional area outlined by subject i mis The mean of is used as the difference validation parameter.

[0075] The embodiment of the present invention obtains a brain reconstructed image, aligns the brain reconstructed image with a standard brain function map, and obtains a target brain function area image; performs three-dimensional reconstruction based on the target brain function area image to obtain a three-dimensional brain function area image; determines a target stimulation area according to the three-dimensional brain function area image, and determines candidate stimulation targets in the target stimulation area based on target setting parameters; adjusts the candidate stimulation targets based on difference verification parameters to obtain a target stimulation target in the target stimulation area, and displays the target stimulation target. By determining the candidate stimulation targets in the brain reconstructed image based on the standard brain function map and then adjusting them to obtain the target stimulation target, the setting of the stimulation target is more accurate.

[0076] Example 2

[0077] Figure 2 This is a flow chart of a method for determining stimulation targets based on brain function maps provided in the second embodiment of the present invention. This embodiment provides a preferred embodiment based on the above solution.

[0078] The present invention proposes to use brain function maps to assist experimenters in locating and outlining brain functional areas for stimulation, and automatically set stimulation targets based on the shapes of the outlined brain functional areas. This provides a low-cost and easily scalable method for locating and outlining brain functional areas for TMS, reduces human errors caused by the process of setting TMS stimulation targets, and thus improves the TMS stimulation effect. The main steps include:

[0079] 1) Brain function mapping and functional area selection

[0080] The brain network atlas published by the Institute of Automation of the Chinese Academy of Sciences in 2016 can be used to locate and delineate the functional areas of the subject's brain. This atlas captures 246 functional brain regions and their connectivity, is 4-5 times more detailed than the traditional Brodmann atlas, and provides objective and precise boundary location. The relevant brain function atlas database has been publicly shared on the corresponding website (http: / / atlas.brainnetome.org).

[0081] 2) Algorithm for localizing and delineating stimulating brain functional areas based on the brain function atlas database

[0082] You can use QT to design a graphical user interface, use the Insight Segmentation and Registration Toolkit (ITK) to complete the registration and alignment of the human head and the stimulation coil, and obtain the relationship between the coil focus coordinate system, head outline, and brain stimulation target in the world coordinate system. Use the Visualization Toolkit (VTK) to complete the modeling and coordinate system transformation of multiple 3D image models, and display the coil, head, and target together in the software interface for precise positioning and navigation.

[0083] To enable brain function atlas-assisted transcranial magnetic stimulation (TMS) brain region delineation, we plan to add two components to the precise positioning and navigation software: 1. Using ITK, we will register the brain function regions in the MNI space of the brain function atlas to the subject space. 2. We will modify the VTK display module to complete the 3D modeling of the brain function regions in the subject space and display them in real time on the software interface.

[0084] The algorithm process of brain functional area registration includes:

[0085] a) Image segmentation: Obtain the MRI image of the subject's brain.

[0086] b) Register the subject's brain image to the MNI152 standard space template and save the registration transformation matrix M at the same time.

[0087] c) Apply the inverse matrix of the transformation matrix M to align the MNI standard brain function areas in the brain function map to the subject space.

[0088] d) Import the subject's brain MRI images and the subject's spatial brain functional area data into the display module and display them using VTK.

[0089] The VTK display module software can display the model through the following steps:

[0090] a) The VTK display module obtains the subject's brain MRI image and the subject's spatial brain functional area data.

[0091] b) Unify the display coordinate systems of the two parts of data and establish a three-dimensional model.

[0092] c) Set model display parameters through various filters and display the model in real time on the software interface.

[0093] 3) Process for setting stimulation targets based on brain functional areas

[0094] First, an image segmentation method is used to obtain an MRI image of the subject's brain. The subject's brain image is registered to the MNI152 standard spatial template, and the registration transformation matrix M is saved. Edge extraction is performed to obtain the distribution of the subject's cerebral cortex in the standard space. The intersection of the spatial distribution of the functional brain areas in the standard space and the spatial distribution of the cerebral cortex is calculated to obtain the cortical spatial distribution of the functional brain areas. The cortical distribution of the functional brain areas in all layers is calculated to obtain the three-dimensional spatial distribution of the cortex of the functional brain areas. The center of the three-dimensional spatial distribution of the functional brain areas is calculated, and based on the target spacing d, the number of target matrix rows m, and the number of columns n set by user interaction, the stimulation targets are automatically arranged in a rectangular shape from the center outward, and the spatial position of each target is calculated. Finally, using the previously saved registration matrix M, an inverse transformation is performed to obtain the position of the stimulation target in the subject's space.

[0095] Because this method sets stimulation targets based on a brain function map in a standard space, even if the subjects' brains differ in shape and size, each stimulation target for each subject can correspond to a specific position in the standard space, providing a consistent target setting standard for subsequent experiments and data processing.

[0096] After the target is set, the target is adjusted based on the predetermined difference verification parameters to obtain the target stimulation target.

[0097] The difference verification parameters can be obtained by an individual difference verification method, which may include the following steps:

[0098] (1) Experimental subjects

[0099] Ten healthy adults (aged 20-30) were recruited as experimental subjects, including five men and five women, all right-handed. Five experienced male TMS experimenters aged around 30 were also recruited.

[0100] (2) Subject MRI image data acquisition

[0101] A GE 3.0T Signa HDX magnetic resonance scanner and an eight-channel phased array coil for the head were used. All subjects were in the supine position. A sponge pad was filled in the gap between the subject's head and the coil to stabilize the head and reduce the impact of head movement on image quality; earplugs were used to reduce machine noise during the scan. After confirming that the subjects had no intracranial organic lesions through routine T1WI examination, these subjects underwent 3D high-resolution T1WI structural imaging. The image acquisition parameters were: repetition time TR = 7.8ms, echo time TE = 3.0ms, inversion time TI = 450ms, inversion angle FA = 13°, layer thickness 1mm, field of view FOV = 256*256mm 2 , matrix 256*256, number of layers is 188.

[0102] (3) Brain functional area delineation and target setting

[0103] The 3D high-resolution T1 / W1 structural images acquired from the subject's scan were imported into the Precision Positioning Navigation software. Two functional areas (A4ul_1 for the left upper limb motor area and A4ul_r for the right upper limb motor area) from the brain functional atlas were used to delineate the subject's brain and displayed in different colors. The stimulation target matrix positions for the two functional areas were then calculated based on the stimulation target setting method for each functional area, and each stimulation target was numbered. Finally, a three-dimensional model constructed from the subject's T1 / W1 image, the two functional areas, and the two target matrices was displayed on the Precision Positioning Navigation software interface.

[0104] (4) Comparison of the accuracy and stability of the two target setting methods

[0105] Standard navigated transcranial magnetic stimulation (TMS) experimental methods were used to register the coil and the subject's head. Myoelectric electrodes were attached to the first dorsal interosseous muscle of the right hand, and MEPs were recorded using a four-channel digital myoelectric and evoked potential (MEP) recorder (Micromed, Italy). TMS stimulation was delivered using a Rapid2 transcranial magnetic stimulator. While obtaining the subject's resting motor threshold, the stimulation coil was kept tangential to the scalp, with the coil handle facing backward and at a 45-degree angle to the longitudinal fissure. Based on the stimulation target matrix set in the left upper limb motor area A4ul_1, the cortical location was identified where, at minimum TMS output, 10 TMS stimulations produced at least five MEPs with an amplitude greater than or equal to 50 μV. This TMS output intensity was considered the subject's resting motor threshold (RMT). This cortical location was the primary motor cortex of the hand.

[0106] Five TMS operators used a conventional target placement method and the target placement method proposed in an embodiment of the present invention to set a stimulation target in the motor function area A4ul_1 of the left upper limb for each subject. The subjects' resting motor thresholds (RMTs) and the coordinates of the target stimulation point in the primary motor cortex of the hand were obtained. The variances of the resting motor thresholds (RMTs) and the coordinates of the target stimulation point in the primary motor cortex of the hand were calculated for each subject using the two target placement methods.

[0107] (5) Obtaining individual differences in the distribution range of MEP stimulation brain areas on standard brain maps

[0108] Electromyographic electrodes were fixed to the first dorsal interosseous muscles of each hand. Using a target placement method based on brain functional areas, stimulation targets were placed in motor functional areas A4ul_l and A4ul_r of each subject's left and right upper limbs. Target spacing was 2 mm, and the matrix size completely covered the stimulated brain functional area. The outermost target in the matrix was kept at least 4 mm away from the functional area. To ensure target positioning accuracy, the subject's head was secured with a bracket. After positioning the magnetic stimulation coil to the target using a robotic arm, the robotic arm was fine-tuned to maintain target positioning accuracy within 1 mm. Using 120% of the resting motor threshold, 10 TMS stimulations were administered to each stimulation target. The MEP intensity, S, and occurrence probability, P, were recorded. The intensity probability, Ps, was defined as P*S.

[0109] According to the above formula (1), the mean and variance of the distance between the target coordinates of the maximum MEP intensity probability Ps obtained in the left and right upper limb motor function areas A4ul_l and A4ul_r of the subject and the center of the brain function area are counted to obtain the individual differences in the maximum MEP position coordinates. According to the above formula (2), the number of target points N with the MEP intensity probability Ps>0.5*max(Ps) obtained in the left and right upper limb motor function areas A4ul_l and A4ul_r of the subject i is counted. i The variance of the MEP half-wave intensity distribution range is obtained by calculating the individual differences. According to the above formula (3), the number of target points with MEP intensity probability Ps>0.5*max(Ps) obtained in the motor function areas A4ul_l and A4ul_r of the left and right upper limbs of the subject, located outside the brain function area outlined by the subject i, is counted. mis The mean of . Get the difference validation parameter.

[0110] The embodiments of the present invention use brain function maps to assist experimenters in locating and outlining brain functional areas for stimulation, and automatically set stimulation targets based on the shapes of the outlined brain functional areas, thereby providing a low-cost and easy-to-promote method for locating and outlining brain functional areas for TMS, reducing human errors caused by the process of setting TMS stimulation targets, and thus improving the TMS stimulation effect.

[0111] Example 3

[0112] Figure 3 This is a schematic diagram of the structure of a device for determining a stimulation target based on a brain function map provided by the third embodiment of the present invention. The device for determining a stimulation target based on a brain function map can be implemented in software and / or hardware. For example, the device for determining a stimulation target based on a brain function map can be configured in a computer device. Figure 3 As shown, the apparatus includes a brain functional area registration module 310, a three-dimensional reconstruction module 320, a candidate target determination module 330, and a target target determination module 340, wherein:

[0113] The brain function area registration module 310 is used to obtain a brain reconstruction image, register the brain reconstruction image with a standard brain function atlas, and obtain a target brain function area image;

[0114] A three-dimensional reconstruction module 320 is used to perform three-dimensional reconstruction based on the target brain functional area image to obtain a three-dimensional brain functional area image;

[0115] A candidate target determination module 330 is configured to determine a target stimulation area based on the three-dimensional brain functional area image and determine candidate stimulation targets in the target stimulation area based on target setting parameters;

[0116] The target point determination module 340 is used to adjust the candidate stimulation target points based on the difference verification parameters, obtain the target stimulation target points in the target stimulation area, and display the target stimulation target points.

[0117] The embodiment of the present invention obtains a brain reconstructed image, aligns the brain reconstructed image with a standard brain function map, and obtains a target brain function area image; performs three-dimensional reconstruction based on the target brain function area image to obtain a three-dimensional brain function area image; determines a target stimulation area according to the three-dimensional brain function area image, and determines candidate stimulation targets in the target stimulation area based on target setting parameters; adjusts the candidate stimulation targets based on difference verification parameters to obtain a target stimulation target in the target stimulation area, and displays the target stimulation target. By determining the candidate stimulation targets in the brain reconstructed image based on the standard brain function map and then adjusting them to obtain the target stimulation target, the setting of the stimulation target is more accurate.

[0118] Optionally, based on the above solution, the brain functional area registration module 310 is specifically configured to:

[0119] Register the reconstructed brain image to the standard space template and determine the registration transformation matrix;

[0120] Based on the registration transformation matrix, the standard brain function areas in the standard brain function atlas are registered to the coordinate system of the brain reconstructed image to obtain the target brain function area image.

[0121] Optionally, based on the above solution, the candidate target determination module is specifically used to:

[0122] The area corresponding to the stimulation functional area in the three-dimensional brain functional area image is used as the target stimulation area.

[0123] Optionally, based on the above solution, the target setting parameters include target spacing, target row number, and target column number. The candidate target determination module 330 is specifically configured to:

[0124] Determine the center position of the target stimulation area, set the targets outward based on the target spacing based on the center position, and obtain candidate stimulation targets that meet the number of target rows and target columns.

[0125] Optionally, based on the above solution, the target point determination module 340 is specifically configured to:

[0126] Determine the difference deviation corresponding to the difference verification parameter;

[0127] An adjustment direction is determined based on the difference deviation, and the candidate stimulation target is adjusted according to the adjustment direction to obtain a target stimulation target in the target stimulation area.

[0128] Optionally, based on the above solution, the device further includes a difference deviation determination module, which is used to:

[0129] Obtaining a sample brain reconstructed image, and determining a sample stimulation target based on a sample brain functional area image obtained by registering the sample brain reconstructed image with a standard brain functional atlas;

[0130] Determine the actual stimulation target information according to the motor evoked potential sampled after stimulating the sample stimulation target;

[0131] The difference verification parameters are determined based on the sample stimulation target information and the actual stimulation target information.

[0132] Optionally, based on the above solution, the difference deviation determination module is specifically used to:

[0133] The target position difference is determined based on the actual stimulation target position and the center position of the stimulated brain functional area;

[0134] The target distribution difference is determined based on the number of actual stimulation targets whose actual stimulation target intensity is greater than the set intensity;

[0135] The difference validation parameters are determined based on the differences in target location and target distribution.

[0136] The stimulation target determination device based on brain function maps provided in an embodiment of the present invention can execute the stimulation target determination method based on brain function maps provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0137] Example 4

[0138] Figure 4 This is a structural diagram of a computer device provided in Example 4 of the present invention. Figure 4 A block diagram of an exemplary computer device 412 suitable for use in implementing embodiments of the present invention is shown. Figure 4 The computer device 412 shown is only an example and should not limit the functionality and scope of use of the embodiments of the present invention.

[0139] like Figure 4As shown, computer device 412 is implemented as a general-purpose computing device. Components of computer device 412 may include, but are not limited to, one or more processors 416, a system memory 428, and a bus 418 that connects various system components (including system memory 428 and processor 416).

[0140] Bus 418 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 local bus to processor 416, or a bus using any of a variety of bus architectures. Examples of 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.

[0141] The computer device 412 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computer device 412, including volatile and non-volatile media, removable and non-removable media.

[0142] System memory 428 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 430 and / or cache memory 432. Computer device 412 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage device 434 may be configured to read and write non-removable, non-volatile magnetic media ( Figure 4 Not shown, often called a "hard drive"). Although Figure 4 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 418 via one or more data media interfaces. Memory 428 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of various embodiments of the present invention.

[0143] A program / utility 440 having a set (at least one) of program modules 442 may be stored, for example, in memory 428. Such program modules 442 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may include an implementation of a network environment. Program modules 442 generally implement the functions and / or methodologies of the embodiments described herein.

[0144] The computer device 412 can also communicate with one or more external devices 414 (e.g., a keyboard, pointing device, display 424, etc.), one or more devices that enable a user to interact with the computer device 412, and / or any device that enables the computer device 412 to communicate with one or more other computing devices (e.g., a network card, a modem, etc.). Such communication can occur via an input / output (I / O) interface 422. Furthermore, the computer device 412 can communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network such as the Internet) via a network adapter 420. As shown, the network adapter 420 communicates with the other modules of the computer device 412 via a bus 418. It should be understood that, although not shown, other hardware and / or software modules can be used in conjunction with the computer device 412, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0145] The processor 416 executes various functional applications and data processing by running programs stored in the system memory 428, such as implementing the method for determining stimulation targets based on brain function maps provided in an embodiment of the present invention, which includes:

[0146] Obtaining a brain reconstruction image, registering the brain reconstruction image with a standard brain function atlas, and obtaining an image of the target brain functional area;

[0147] Perform three-dimensional reconstruction based on the target brain functional area image to obtain a three-dimensional brain functional area image;

[0148] Determine the target stimulation area based on the three-dimensional brain functional area image, and determine the candidate stimulation targets in the target stimulation area based on the target setting parameters;

[0149] The candidate stimulation targets are adjusted based on the difference verification parameters to obtain the target stimulation targets in the target stimulation area, and the target stimulation targets are displayed.

[0150] Of course, those skilled in the art will appreciate that the processor may also implement the technical solution of the method for determining stimulation targets based on brain function maps provided in any embodiment of the present invention.

[0151] Example 5

[0152] The fifth embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for determining stimulation targets based on brain function maps provided in the embodiment of the present invention is implemented. The method includes:

[0153] Obtaining a brain reconstruction image, registering the brain reconstruction image with a standard brain function atlas, and obtaining an image of the target brain functional area;

[0154] Perform three-dimensional reconstruction based on the target brain functional area image to obtain a three-dimensional brain functional area image;

[0155] Determine a target stimulation area according to the three-dimensional brain functional area image, and determine candidate stimulation targets in the target stimulation area based on target point setting parameters;

[0156] The candidate stimulation target is adjusted based on the difference verification parameter to obtain the target stimulation target of the target stimulation area, and the target stimulation target is displayed.

[0157] Of course, the computer-readable storage medium provided by an embodiment of the present invention stores a computer program which is not limited to the above method operations, but can also execute related operations of the stimulation target determination method based on brain function maps provided by any embodiment of the present invention.

[0158] The computer storage medium of the embodiment of the present invention may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device.

[0159] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0160] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0161] Computer program code for carrying out the operations of the present invention may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on the remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0162] Note that the above are only preferred embodiments of the present invention and the technical principles employed. Those skilled in the art will appreciate that the present invention is not limited to the specific embodiments herein, and that various obvious changes, readjustments, and substitutions are possible for those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments and may include many other equivalent embodiments without departing from the scope of the present invention. The scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for determining stimulation targets based on brain function maps, characterized in that: include: Acquiring a brain reconstructed image, and registering the brain reconstructed image with a standard brain function atlas to obtain an image of a target brain function area; Performing three-dimensional reconstruction based on the target brain functional area image to obtain a three-dimensional brain functional area image; Determine a target stimulation area according to the three-dimensional brain functional area image, and determine candidate stimulation targets in the target stimulation area based on target point setting parameters; Adjusting the candidate stimulation target based on the difference verification parameter to obtain a target stimulation target in the target stimulation area, and displaying the target stimulation target; wherein the difference verification parameter is a positional deviation between the candidate stimulation target and the target stimulation target; The method further comprises: Acquiring a sample brain reconstructed image, and determining a sample stimulation target based on a sample brain functional area image obtained by registering the sample brain reconstructed image with a standard brain function atlas; determining actual stimulation target information according to the motor evoked potential sampled after stimulating the sample stimulation target; A difference verification parameter is determined based on the sample stimulation target information and the actual stimulation target information.

2. The method according to claim 1, characterized in that The registering the reconstructed brain image with a standard brain function atlas to obtain a target brain function area image includes: registering the reconstructed brain image to a standard space template and determining a registration transformation matrix; Based on the registration transformation matrix, the standard brain function area in the standard brain function atlas is registered to the coordinate system of the brain reconstructed image to obtain the target brain function area image.

3. The method according to claim 1, characterized in that Determining the target stimulation area according to the three-dimensional brain functional area image includes: The area corresponding to the stimulation functional area in the three-dimensional brain functional area image is used as the target stimulation area.

4. The method according to claim 1, wherein The target point setting parameters include target point spacing, target point row number, and target point column number. The determining of candidate stimulation targets in the target stimulation area based on the target point setting parameters includes: The center position of the target stimulation area is determined, and the target points are set outward based on the target point spacing with the center position as a reference to obtain candidate stimulation target points that meet the target point row number and the target point column number.

5. The method according to claim 1, wherein The step of adjusting the candidate stimulation target based on the difference verification parameter to obtain the target stimulation target in the target stimulation area includes: Determining a difference deviation corresponding to the difference verification parameter; An adjustment orientation is determined based on the difference deviation, and the candidate stimulation target is adjusted according to the adjustment orientation to obtain a target stimulation target in the target stimulation area.

6. The method according to claim 1, wherein The actual stimulation target information includes an actual stimulation target position and an actual stimulation target intensity, and determining a difference verification parameter based on the sample stimulation target information and the actual stimulation target information includes: The target position difference is determined based on the actual stimulation target position and the center position of the stimulated brain functional area; The target distribution difference is determined based on the number of actual stimulation targets whose actual stimulation target intensity is greater than the set intensity; The difference verification parameter is determined according to the target position difference and the target distribution difference.

7. A device for determining stimulation targets based on brain function maps, characterized in that: include: A brain function area registration module is used to obtain a brain reconstructed image, register the brain reconstructed image with a standard brain function atlas, and obtain a target brain function area image; A three-dimensional reconstruction module, configured to perform three-dimensional reconstruction based on the target brain functional area image to obtain a three-dimensional brain functional area image; a candidate target determination module, configured to determine a target stimulation area according to the three-dimensional brain functional area image, and determine candidate stimulation targets in the target stimulation area based on target setting parameters; a target point determination module, configured to adjust the candidate stimulation target point based on a difference verification parameter to obtain a target stimulation target point in the target stimulation area, and display the target stimulation target point; wherein the difference verification parameter is a positional deviation between the candidate stimulation target point and the target stimulation target point; The device further comprises: A difference deviation determination module is used to obtain a sample brain reconstructed image, determine a sample stimulation target based on a sample brain functional area image obtained by registering the sample brain reconstructed image with a standard brain functional map; determine actual stimulation target information based on the motor evoked potential sampled after stimulating the sample stimulation target; and determine a difference verification parameter based on the sample stimulation target information and the actual stimulation target information.

8. A device for determining stimulation targets based on brain function maps, characterized in that: The device comprises: one or more processors; a storage device for storing one or more programs; a display for displaying images; When one or more programs are executed by one or more processors, the one or more processors implement the method for determining stimulation targets based on brain function maps as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for determining stimulation targets based on brain function maps as described in any one of claims 1 to 6 is implemented.

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