Intracranial microneedle implantation auxiliary methods and systems

Abstract

This disclosure provides an intracranial microneedle implantation assistance method, comprising: determining the positions of each target functional area corresponding to the current microneedle implantation and the positions of each sensitive area contained within each target functional area in a three-dimensional reconstruction model of the brain of the target object; determining a pre-implanted three-dimensional area within a target three-dimensional area composed of all the target functional areas, wherein the pre-implanted three-dimensional area is shaped as a quadrangular prism and the extension direction of the side edges is a preset implantation direction corresponding to the current microneedle implantation; adjusting the position of at least one face and / or at least one side edge of the pre-implanted three-dimensional area by translating it toward the centroid of the pre-implanted three-dimensional area to obtain a final implanted three-dimensional area, wherein the final implanted three-dimensional area does not overlap with any of the sensitive areas.

Description

Technical Field

[0001] This disclosure relates to the field of medical technology assistance technology, and in particular to an intracranial microneedle implantation assistance method and system. Background Technology

[0002] Brain-computer interface (BCI) microneedle implantation connects the implanted device to external specialized medical devices, enabling the collection of physiological and pathological information such as the patient's brain waves and pupils. This information can be used by the medical team to monitor the patient's condition in a timely manner, accumulate more clinical experience, and send alerts based on data changes to save the patient's life in a timely manner.

[0003] In related technologies, the intracranial microneedle implantation area needs to be confirmed before microneedle implantation. Specifically, the target functional area corresponding to the current microneedle implantation is first determined according to the needs, and then medical personnel roughly determine a microneedle implantation area in the cranium based on their personal experience, which can meet the signal acquisition of all target functional areas. This method of determining the microneedle implantation area based on human experience has the following drawbacks: First, it requires a high level of skill from medical personnel; second, the accuracy of the manually estimated microneedle implantation area is not high; third, because there may be some differences in intracranial structure among different individuals, the microneedle implantation area estimated based on experience may not be suitable for some subjects. Summary of the Invention

[0004] This disclosure aims to address at least one of the technical problems existing in the prior art, and proposes an intracranial microneedle implantation auxiliary method and auxiliary system.

[0005] In a first aspect, embodiments of this disclosure provide an intracranial microneedle implantation assistance method, including:

[0006] Within the three-dimensional reconstruction model of the target brain, the locations of each target functional area corresponding to the current microneedle implantation and the locations of each sensitive area contained within each target functional area are determined.

[0007] A pre-implanted three-dimensional region is determined within the target three-dimensional region composed of all the target functional areas. The pre-implanted three-dimensional region is shaped like a quadrangular prism and the extension direction of the side edges is a preset implantation direction corresponding to the current microneedle implantation.

[0008] The position of at least one face and / or at least one side edge of the pre-implanted three-dimensional region is adjusted by translating it in a direction closer to the centroid of the pre-implanted three-dimensional region, so as to obtain the final implanted three-dimensional region, which does not overlap with any of the sensitive regions.

[0009] In some embodiments, the step of determining the pre-implanted three-dimensional region within the target three-dimensional region comprised of all the target functional regions includes:

[0010] Within the target three-dimensional region, a cuboid region with the largest volume that extends along the preset direction and surrounds the centroid of the target three-dimensional region is identified as the pre-implanted three-dimensional region.

[0011] In some embodiments, the pre-implanted three-dimensional region has four side edges, four long edges, and four wide edges, and the extension directions of the side edges, the extension directions of the long edges, and the extension directions of the wide edges are each configured with corresponding preset distance constants.

[0012] The step of adjusting the position of at least one face and / or at least one side edge of the pre-implanted three-dimensional region by translating it toward the centroid of the pre-implanted three-dimensional region includes:

[0013] At least one face of the pre-implanted three-dimensional region is translated toward the centroid of the pre-implanted three-dimensional region to determine the largest cuboid region in the non-sensitive region of the target three-dimensional region, excluding the sensitive region, as the first corrected implanted three-dimensional region;

[0014] Based on the implantation difficulty coefficient corresponding to the current microneedle implantation obtained in advance, the safety distance corresponding to each face of the first modified implantation three-dimensional area is calculated. The safety distance is equal to the preset distance constant configured in the normal direction of the corresponding face multiplied by the implantation difficulty coefficient.

[0015] Each face of the first modified implanted three-dimensional region is taken as the face to be adjusted, and it is determined whether the minimum distance between the avoidance area composed of all the sensitive areas and the face to be adjusted is less than the safe distance corresponding to the face to be adjusted.

[0016] If so, the surface to be adjusted is translated toward the centroid of the pre-implanted three-dimensional area until the minimum distance between the avoidance area and the surface to be adjusted is equal to the safe distance corresponding to the surface to be adjusted.

[0017] If not, keep the surface to be adjusted unchanged;

[0018] The first corrected implantation three-dimensional region after the safety distance adjustment is completed is used as the second corrected implantation three-dimensional region, and the final implantation three-dimensional region is obtained based on the second corrected implantation three-dimensional region.

[0019] In some embodiments, the step of obtaining the final implanted three-dimensional region based on the second modified implanted three-dimensional region includes:

[0020] In response to the fact that the number of target functional areas corresponding to the current microneedle implantation is 1, the second modified implantation three-dimensional area is taken as the final implantation three-dimensional area;

[0021] Alternatively, in response to the fact that the number of target functional areas corresponding to the current microneedle implantation is greater than 1, the cross-functional area coefficient corresponding to the current microneedle implantation is determined. The cross-functional area coefficient is equal to the product of the square root of the number of target functional areas and the standard deviation of the distance between the centroid of each target functional area and the centroid of the second modified implantation three-dimensional area.

[0022] Obtain the centroid offset relative distance corresponding to the second corrected implanted three-dimensional region. The centroid offset relative distance is the distance between the centroid of the largest region enclosed by the line connecting the projection points of the centroids of the target functional regions on the virtual target plane when the centroids of the second corrected implanted three-dimensional region and the centroids of each target functional region are projected along the extension direction of the side edge of the pre-implanted three-dimensional region to the virtual target plane, and the projection point of the centroid of the second corrected implanted three-dimensional region on the virtual target plane. The virtual target plane is a virtual plane perpendicular to the extension direction of the side edge of the pre-implanted three-dimensional region.

[0023] Detect whether the product of the centroid offset relative distance and the cross-functional zone coefficient is greater than a preset offset distance threshold;

[0024] If so, a translation method is adopted in the direction closer to the virtual central axis to adjust at least one side edge of the second corrected implanted three-dimensional region, and the second corrected implanted three-dimensional region that has completed side edge adjustment and meets the preset conditions and has the largest volume is taken as the final implanted three-dimensional region. The preset conditions are: the product of the centroid offset relative distance corresponding to the second corrected implanted three-dimensional region that has completed side edge adjustment and the cross-functional region coefficient is less than or equal to the preset offset distance threshold.

[0025] If not, then the second modified implanted three-dimensional region will be used as the final implanted three-dimensional region.

[0026] In some embodiments, prior to adjusting the position of at least one surface and / or at least one side edge of the pre-implanted three-dimensional region by translating it toward the centroid of the pre-implanted three-dimensional region to obtain the corrected implanted three-dimensional region, the method further includes:

[0027] Based on the location of each target functional area and the location of each sensitive area contained within each target functional area, the implantation difficulty coefficient corresponding to the current microneedle implantation is determined.

[0028] In some embodiments, the step of determining the location of each target functional area corresponding to the current microneedle implantation and the location of each sensitive area contained within each target functional area within a three-dimensional reconstruction model of the target object's brain includes:

[0029] Acquire a set of brain tomographic images of the target object, the set of brain tomographic images including tomographic images of the target object's brain at multiple different scanning layers;

[0030] Target functional area detection and sensitive area detection are performed on each of the tomographic scan images to obtain the two-dimensional position information of each target functional area corresponding to the current microneedle implantation in each tomographic scan image, as well as the two-dimensional position information of the sensitive areas contained in each target functional area.

[0031] Based on the brain tomographic image set and the target functional area detection results and sensitive area detection results of each tomographic image, a three-dimensional reconstruction is performed to obtain the brain three-dimensional reconstruction model, the three-dimensional position information of each target functional area in the three-dimensional reconstruction model, and the three-dimensional position information of the sensitive areas contained in each target functional area in the three-dimensional reconstruction model.

[0032] The steps for determining the implantation difficulty coefficient corresponding to the current microneedle implantation, based on the location of each target functional area and the location of each sensitive area contained within each target functional area, include:

[0033] Determine the regional difficulty coefficient corresponding to each of the target functional areas;

[0034] Based on the regional difficulty coefficient corresponding to each of the target functional areas, the implantation difficulty coefficient corresponding to the current microneedle implantation is determined, and the implantation difficulty coefficient is the maximum value among all the regional difficulty coefficients corresponding to the target functional areas;

[0035] The step of determining the regional difficulty coefficient corresponding to a target functional area includes:

[0036] In each of the tomographic scan images, the cross-sectional proportion of the sensitive area corresponding to multiple different measurement positions of the target functional area at the first preset direction is obtained by using an equal-interval measurement method along the first preset direction. The cross-sectional proportion of the sensitive area is equal to the ratio of the sum of the widths of all the sensitive areas contained in the target functional area at the corresponding measurement positions along the second preset direction to the width of the entire target functional area at the corresponding measurement positions along the second preset direction. The first preset direction intersects with the second preset direction.

[0037] Select the largest cross-sectional percentage of the sensitive area from all the cross-sectional percentages of the sensitive areas corresponding to the target functional area, and use it as the first difficulty coefficient corresponding to the target functional area;

[0038] Based on the three-dimensional position information of the target functional area in the three-dimensional reconstruction model and the three-dimensional position information of all the sensitive areas contained in the target functional area in the three-dimensional reconstruction model, a second difficulty coefficient corresponding to the target functional area is determined. The second difficulty coefficient is equal to the ratio of the sum of the volumes of all the sensitive areas contained in the target functional area in the three-dimensional reconstruction model to the volume of the target functional area in the three-dimensional reconstruction model.

[0039] The regional difficulty coefficient corresponding to the target functional area is determined based on the first difficulty coefficient and the second difficulty coefficient, and the implantation difficulty coefficient is equal to the product of the first difficulty coefficient and the second difficulty coefficient.

[0040] In some embodiments, after obtaining the final implanted three-dimensional region, the method further includes:

[0041] Based on the final implantation three-dimensional region and the pre-acquired target microneedle type for the current microneedle implantation, the microneedle clamping module is controlled to select a target microneedle from the microneedle platform that is of the target microneedle type and whose size is sufficient to be placed within the final implantation three-dimensional region.

[0042] In some embodiments, after obtaining the final implanted three-dimensional region, the method further includes:

[0043] During the implantation process of inserting the target microneedle into the target object, the imaging module captures images of the target microneedle and the brain of the target object in real time as images of the implantation process;

[0044] Using the image portion of the target object's brain in the implantation process image, the implantation process image is image registered with the three-dimensional reconstruction model of the target object's brain, and the target microneedle is mapped into the three-dimensional reconstruction model of the brain;

[0045] The actual implantation direction corresponding to the target microneedle in the brain three-dimensional reconstruction model is detected, and it is determined whether the angle between the actual implantation direction and the extension direction of the side edge of the final implanted three-dimensional area is greater than a preset angle threshold. When it is determined that the angle between the actual implantation direction and the extension direction of the side edge of the final implanted three-dimensional area is greater than the preset angle threshold, a first reminder message is generated to indicate that the implantation direction has deviated.

[0046] And / or, based on the two selected implantation process images, the implantation speed of the target microneedle is obtained, and it is determined whether the implantation speed is greater than a preset speed threshold. When it is determined that the implantation speed is greater than the preset speed threshold, a second reminder message is generated to characterize the implantation speed exceeding the threshold. The implantation speed is equal to the difference between the length of the target microneedle outside the target brain in the first frame of the implantation process image taken and the length of the target microneedle outside the target brain in the second frame of the implantation process image taken, divided by the difference in the shooting time of the two frames of the implantation process image.

[0047] And / or, in the implantation process image of the current frame, obtain the length of the target microneedle outside the brain of the target object, calculate the ratio of the length of the target microneedle outside the brain of the target object to the total length of the target microneedle as the remaining implantation progress, and determine whether the remaining implantation progress is less than a preset progress threshold, and when it is determined that the remaining implantation progress is less than the preset progress threshold, generate a third reminder message to indicate that the implantation depth is relatively deep, and in response to the remaining implantation progress being 0, generate a fourth reminder message to indicate that the microneedle has been completely implanted.

[0048] In some embodiments, the implantation process of implanting the target microneedle into the target object further includes:

[0049] Record and store the actual implantation direction, implantation speed, and / or remaining implantation progress at different moments during the implantation process.

[0050] Secondly, this disclosure also provides an intracranial microneedle implantation assistance system, comprising:

[0051] The detection module is configured to determine the location of each target functional area corresponding to the current microneedle implantation and the location of each sensitive area contained within each target functional area within the three-dimensional reconstruction model of the target object's brain;

[0052] The determination module is configured to determine a pre-implanted three-dimensional area within the target three-dimensional area composed of all the target functional areas, wherein the shape of the pre-implanted three-dimensional area is a quadrangular prism and the extension direction of the side edges is a preset implantation direction corresponding to the current microneedle implantation.

[0053] The adjustment module is configured to adjust the position of at least one face and / or at least one side edge of the pre-implanted three-dimensional region by translating it in a direction closer to the centroid of the pre-implanted three-dimensional region, so as to obtain the final implanted three-dimensional region, wherein the final implanted three-dimensional region does not overlap with any of the sensitive regions. Attached Figure Description

[0054] Figure 1A flowchart of an intracranial microneedle implantation auxiliary method provided in this disclosure embodiment;

[0055] Figure 2 This is a flowchart of an optional implementation method of step S1 in this embodiment of the present disclosure;

[0056] Figure 3 This is a flowchart of an optional implementation method of step S3 in this embodiment of the present disclosure;

[0057] Figure 4 This is a flowchart of an optional implementation method of step S306 in the embodiments of this disclosure;

[0058] Figure 5 A flowchart of another intracranial microneedle implantation auxiliary method provided in this disclosure embodiment;

[0059] Figure 6 This is a schematic diagram illustrating the cross-sectional proportion of the sensitive area corresponding to multiple different measurement positions in a tomographic image of a target functional area in an embodiment of this disclosure.

[0060] Figure 7 A flowchart illustrating yet another intracranial microneedle implantation assistance method provided in this disclosure embodiment;

[0061] Figure 8 A structural block diagram of an intracranial microneedle implantation assist system provided in this disclosure embodiment;

[0062] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0063] To enable those skilled in the art to better understand the technical solutions of this disclosure, the disclosure will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0064] Unless otherwise defined, the technical or scientific terms used in this disclosure shall have the ordinary meaning understood by one of ordinary skill in the art to which this disclosure pertains. The terms “first,” “second,” and similar terms used in this disclosure do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Similarly, the terms “an,” “a,” or “the,” and similar terms do not indicate a quantity limitation, but rather indicate the presence of at least one. The terms “including,” “comprising,” or “containing,” and similar terms mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as “upper,” “lower,” “left,” and “right,” are used only to indicate relative positional relationships, and these relative positional relationships may change accordingly when the absolute position of the described object changes.

[0065] In the various figures, the same elements are represented by similar reference numerals. For clarity, not all parts in the figures are drawn to scale. Furthermore, some well-known parts may not be shown in the figures.

[0066] Many specific details of this disclosure, such as the structure, materials, dimensions, processing methods, and techniques of the components, are described below to provide a clearer understanding of the disclosure. However, as those skilled in the art will understand, this disclosure may be implemented without following these specific details.

[0067] Modern medicine has divided the entire brain into functional areas, such as the motor cortex (controlling voluntary movement on the opposite side), the visual cortex (controlling eye and head / neck rotation), the motor language cortex (responsible for speech pronunciation), the writing cortex (controlling writing ability), the tactile cortex (controlling tactile ability), the auditory-verbal cortex (controlling auditory ability), the visual processing cortex (responsible for visual processing), and the balance control cortex (controlling body balance), etc.

[0068] Sensitive areas refer to regions within functional zones that are crucial for specific functions and whose damage could lead to severe functional impairment, such as vascular areas or scar areas within functional zones. In this disclosure, these are areas within functional zones where microneedles cannot be implanted. Sensitive areas within each functional zone can be predefined manually.

[0069] In practical applications, each microneedle implantation has a corresponding target functional area, which is the functional area that can be stimulated or receive corresponding signals using the microneedle electrode. For example, if a microneedle electrode Q is needed to stimulate functional areas A and B or receive corresponding signals, then a single microneedle implantation operation is required to implant the microneedle electrode Q into a region within the cranium capable of sending signals to or acquiring signals from functional areas A and B (generally within the area formed by functional areas A and B). In other words, the microneedle implantation of the microneedle electrode Q corresponds to two target functional areas: functional area A and functional area B.

[0070] Furthermore, although there are some differences in the intracranial structure among different individuals, the approximate locations of various functional areas within the skull are similar. For example, the cortical motor function area and visual center function area are both located in the frontal lobe, the tactile center function area is located in the parietal lobe, the auditory speech center function area is located in the temporal lobe, the visual processing function area is located in the occipital lobe, and the body balance control function area is located in the thalamus. Therefore, once the target functional area corresponding to a particular microneedle implantation is determined, a general microneedle implantation direction can be determined based on the intracranial location of these target functional areas, i.e., the preset implantation direction described below.

[0071] The centroid of a two-dimensional or three-dimensional graphic described in this disclosure specifically refers to the center of gravity of the corresponding graphic (with a uniformly distributed mass density inside the graphic).

[0072] Figure 1 This is a flowchart illustrating an intracranial microneedle implantation assistance method provided in an embodiment of this disclosure. Figure 1 As shown, this intracranial microneedle implantation assistance method includes:

[0073] Step S1: Determine the location of each target functional area corresponding to the current microneedle implantation and the location of each sensitive area contained within each target functional area in the three-dimensional reconstruction model of the target object's brain.

[0074] In this embodiment of the disclosure, the brain of the target object can be modeled using brain three-dimensional reconstruction technology to obtain a brain three-dimensional reconstruction model of the target object, and the location of each target functional area corresponding to the current microneedle implantation and the location of each sensitive area contained in each target functional area can be determined in the brain three-dimensional reconstruction model.

[0075] Step S2: Determine the pre-implanted three-dimensional region within the target three-dimensional region composed of all target functional regions.

[0076] The pre-implanted three-dimensional area is shaped like a quadrangular prism, and the extension direction of the side edges is a preset implantation direction corresponding to the current microneedle implantation. This preset implantation direction can be determined manually in advance.

[0077] The pre-implanted three-dimensional region can be determined manually within the target three-dimensional region (e.g., a quadrangular prism region is drawn manually within the target three-dimensional region using an input device as the pre-implanted three-dimensional region), or it can be automatically generated within the target three-dimensional region based on certain algorithms (see below). In this disclosure, it is only necessary to ensure that the pre-implanted three-dimensional region is located within the target three-dimensional region and that the extension direction of the side edges is the pre-given preset implantation direction.

[0078] In practical applications, the minimum size of the pre-implanted three-dimensional region can be limited according to actual needs. For example, the length of the side edge of the pre-implanted three-dimensional region cannot be less than a first length threshold, the length of the long edge of the pre-implanted three-dimensional region cannot be less than a second length threshold, and the length of the wide edge of the pre-implanted three-dimensional region cannot be less than a third length threshold. The first, second, and third length thresholds can all be set as needed. In principle, to meet the size requirements of microneedles, the larger the pre-implanted three-dimensional region, the better.

[0079] Step S3: Adjust the position of at least one face and / or at least one side edge of the pre-implanted three-dimensional region by translating it in a direction closer to the centroid of the pre-implanted three-dimensional region, so as to obtain the final implanted three-dimensional region. The final implanted three-dimensional region does not overlap with any of the sensitive regions.

[0080] In step S3, by translating at least one face and / or at least one side edge of the pre-implanted three-dimensional region toward the centroid of the pre-implanted three-dimensional region, the pre-implanted three-dimensional region can be reduced in size and effectively avoid sensitive areas, thus obtaining the final implanted three-dimensional region.

[0081] The technical solution disclosed herein involves performing three-dimensional reconstruction of the brain of the target object and obtaining the location of each target functional area corresponding to the current microneedle implantation, as well as the location of each sensitive area contained within each target functional area. Then, a pre-implanted three-dimensional area is determined based on the target three-dimensional area composed of all target functional areas. Finally, the pre-implanted three-dimensional area is modified to avoid sensitive areas, thereby accurately providing the final implanted three-dimensional area for the target object.

[0082] In some embodiments, in step S2, a cuboid region with the largest volume surrounding the centroid of the target three-dimensional region, with a preset direction as the extension direction of its side edges, can be determined within the target three-dimensional region as the pre-implanted three-dimensional region. As described above, the larger the pre-implanted three-dimensional region, the better.

[0083] In some embodiments, the pre-implanted three-dimensional region has four side edges, four long edges, and four wide edges. The extension directions of the side edges, the long edges, and the wide edges are each configured with corresponding preset distance constants. The preset distance constant corresponding to the extension direction of the side edges is denoted as d. H The preset distance constant corresponding to the extension direction of the long edge is denoted as d. L The preset distance constant corresponding to the extension direction of the wide edge is denoted as d. W .

[0084] Figure 2 This is a flowchart of an optional implementation method for step S1 in an embodiment of this disclosure. Figure 2 As shown, in some embodiments, step S1 includes:

[0085] Step S101: Obtain the brain tomography image set of the target object.

[0086] The brain computed tomography (CT) image set includes computed tomography images of the target subject's brain at multiple different scanning layers. These images can be either MRI or CT images.

[0087] Step S102: Target functional area detection and sensitive area detection are performed on each tomographic scan image to obtain the two-dimensional position information of each target functional area corresponding to the current microneedle implantation in each tomographic scan image, as well as the two-dimensional position information of the sensitive areas contained in each target functional area.

[0088] Specifically, corresponding functional area detection models can be pre-trained for different functional areas (generally including sample collection, sample training, etc., and the models can use Unet++, Mask-RCNN, etc.), such as cortical motor functional area detection models, visual center functional area detection models, and motor language center functional area detection models. In step S102, each tomographic image can be detected and identified based on the target functional area detection models corresponding to the current microneedle implantation, thereby obtaining the two-dimensional position information of each target functional area in each tomographic image corresponding to the current microneedle implantation. The two-dimensional position information of each target functional area in each tomographic image can be represented by the set of two-dimensional coordinates of the edge points of each target functional area.

[0089] In addition, one or more sensitive area detection models (such as blood vessel detection models and scar detection models) can be pre-trained. Then, the sensitive area detection models can be used to detect the sensitive areas located within each target functional area in each tomographic image, obtaining the two-dimensional location information of the sensitive areas contained in each target functional area. The two-dimensional location information of each sensitive area within each target functional area in each tomographic image can be represented by the set of two-dimensional coordinates of the edge points of each sensitive area.

[0090] Step S103: Perform three-dimensional reconstruction based on the brain tomographic image set and the detection results of target functional areas and sensitive areas of each tomographic image to obtain a three-dimensional reconstruction model of the brain, as well as the three-dimensional position information of each target functional area and the three-dimensional position information of the sensitive areas contained in each target functional area within the three-dimensional reconstruction model.

[0091] The process of 3D brain reconstruction using tomographic images generally includes: image preprocessing, brain image segmentation, 3D brain reconstruction, and model editing and modification. Image preprocessing involves reducing noise, enhancing contrast, and removing artifacts from the tomographic images to improve image quality. Specialized image processing software (such as MATLAB, ITK-SNAP, and 3D Slicer) can be used for further processing and analysis. Brain image segmentation involves identifying brain boundaries within the tomographic images to determine the brain image regions; this is a fundamental step in constructing the 3D model. Manual segmentation methods can be used, drawing contours to identify brain images; alternatively, automatic segmentation methods, such as thresholding, region growing, and edge detection algorithms, can be used to identify and separate brain images. 3D brain reconstruction refers to the process of converting brain image segmentation results into a 3D model. This can be achieved through various 3D reconstruction techniques, such as voxel-based methods (e.g., McLeod, Raycasting) and surface-based methods (e.g., Marching Cubes, Surface Extraction). The reconstruction process may involve steps such as smoothing the model and removing redundant data to improve model quality. Model editing and repair refer to the necessary editing and repair after creating the 3D reconstructed brain model. This includes removing noise, filling holes, and adjusting structures. Professional 3D modeling software (e.g., Blender, Maya, 3ds Max, VTK) can be used for editing and repair.

[0092] After the three-dimensional reconstruction is completed, not only can the three-dimensional image data of the entire brain be obtained, but also the three-dimensional image data of each target functional area in the brain (that is, the three-dimensional position information of the target functional area can be represented by the three-dimensional coordinate set of the edge points of the target functional area) and the three-dimensional image data of the sensitive areas contained in each target functional area (that is, the three-dimensional position information of the sensitive area can be represented by the three-dimensional coordinate set of the edge points of the sensitive area).

[0093] Figure 3 This is a flowchart illustrating an optional implementation of step S3 in an embodiment of this disclosure. Figure 3 As shown, in some embodiments, step S3, adjusting the position of at least one face and / or at least one side edge of the pre-implanted three-dimensional region by translating it toward the centroid of the pre-implanted three-dimensional region, specifically includes:

[0094] Step S301: Translate at least one face of the pre-implanted three-dimensional region toward the centroid of the pre-implanted three-dimensional region, so as to determine the largest cuboid region in the non-sensitive region of the target three-dimensional region that surrounds the centroid of the target three-dimensional region, and use it as the first corrected implanted three-dimensional region.

[0095] That is, in step S301, by performing surface translation, a cuboid region with the largest volume that surrounds the centroid of the target three-dimensional region is determined from the non-sensitive area.

[0096] Step S302: Based on the implantation difficulty coefficient corresponding to the current microneedle implantation obtained in advance, calculate the safety distance corresponding to each face of the first corrected implantation three-dimensional area.

[0097] The safe distance is equal to the preset distance constant configured in the normal direction of the corresponding surface multiplied by the implantation difficulty coefficient.

[0098] Step S303: Take each face of the first correction implanted three-dimensional area as the face to be adjusted, and determine whether the minimum distance between the avoidance area formed by all sensitive areas and the face to be adjusted is less than the safe distance corresponding to the face to be adjusted.

[0099] If yes, proceed to step S304. If no, proceed to step S305.

[0100] Step S304: Translate the surface to be adjusted toward the centroid of the pre-implanted 3D area until the minimum distance between the avoidance area and the surface to be adjusted is equal to the safe distance corresponding to the surface to be adjusted.

[0101] Step S305: Keep the surface to be adjusted stationary.

[0102] Through steps S303 to S305, the minimum distance from any point on any surface of the first corrected implantation three-dimensional region after the safety distance adjustment to any sensitive region is greater than or equal to the safety distance corresponding to the surface where that point is located. This design ensures that a certain distance is maintained between the first corrected implantation three-dimensional region and the sensitive region in all directions, reserving a certain error allowance for subsequent microneedle implantation.

[0103] After the first correction implantation three-dimensional area has completed the safety distance adjustment, proceed to the next step S306.

[0104] Step S306: Take the first corrected implantation three-dimensional region after the safety distance adjustment is completed as the second corrected implantation three-dimensional region, and obtain the final implantation three-dimensional region based on the second corrected implantation three-dimensional region.

[0105] Figure 4 This is a flowchart of an optional implementation method for step S306 in an embodiment of this disclosure. Figure 4 As shown, in some embodiments, step S306 includes:

[0106] Step S3061a: In response to the fact that the number of target functional areas corresponding to the current microneedle implantation is 1, the second modified implantation three-dimensional area is taken as the final implantation three-dimensional area.

[0107] Step S3061b: In response to the fact that the number of target functional areas corresponding to the current microneedle implantation is greater than 1, determine the cross-functional area coefficient corresponding to the current microneedle implantation.

[0108] Among them, the cross-functional zone coefficient ψ is equal to the square root of the number of target functional zones k and the standard deviation of the distance between the centroid of each target functional zone and the centroid of the second modified implanted three-dimensional zone, and the product of the two.

[0109] The cross-functional zone coefficient ψ can be expressed by the following formula:

[0110]

[0111] Where std() represents the standard deviation function, The centroid O of the i-th target functional area is represented by […]. i The distance between the centroid G1 of the second modified implanted 3D region and the centroid G1, where i is an integer and i∈[1,k].

[0112] In this embodiment of the disclosure, the cross-functional area coefficient is positively correlated with two factors: 1) the number of target functional areas k; 2) the standard deviation of the distance between the centroid of each target functional area and the centroid of the second modified implanted three-dimensional area.

[0113] It should be noted that the more target functional areas k there are, the more factors that need to be considered when implanting microneedles, and the more careful one needs to be in determining the subsequent implantation of the three-dimensional area.

[0114] Standard deviation of the distance between the centroid of each target functional area and the centroid of the second modified implanted three-dimensional area It can reflect, to a certain extent, the distribution of the centroids of each target functional area around the centroid of the second modified implanted three-dimensional area. Among them, the standard deviation... The larger the value, the greater the difference in distance between the centroids of each target functional area on the surface and the centroid of the second corrected implanted three-dimensional region. The more dispersed the centroids of each target functional area are around the centroid of the second corrected implanted three-dimensional region, the more cautious the determination of the subsequent implanted three-dimensional region needs to be; standard deviation The smaller the value, the greater the difference in distance between the centroid of each target functional area on the surface and the centroid of the second modified implanted three-dimensional area, and the more concentrated the centroids of each target functional area are around the centroid of the second modified implanted three-dimensional area.

[0115] Step S3062b: Obtain the relative distance of the centroid offset corresponding to the second corrected implanted three-dimensional region.

[0116] Among them, the centroid offset relative distance For: the centroid G1 of the second modified implanted three-dimensional region, and the centroid O of each target functional region. i When projected onto the virtual target plane along the extension direction of the side edge of the pre-implanted 3D region, the centroids O1 to O2 of each target functional region are... k Projection points O1'~O on the virtual target plane k The centroid O of the largest region enclosed by the lines connecting '~' g ', the distance between the centroid G1 of the second modified implanted three-dimensional region and the projection point G1' of the virtual target plane, the virtual target plane being a virtual plane perpendicular to the extension direction of the side edge of the pre-implanted three-dimensional region.

[0117] It should be noted that when there are two target functional areas, the largest area enclosed by the line connecting the projection points of the centroids of the two target functional areas on the virtual target plane is a line segment.

[0118] When there are 3 target functional areas, the largest area (maximum area) is formed by the lines connecting the centroids of the 3 target functional areas to the projection points on the virtual target plane. This area is a triangular region enclosed by the 3 centroid points (not considering the case where the three points are collinear).

[0119] When the number of target functional areas is greater than 3, the largest area (maximum area) enclosed by the lines connecting the centroids of multiple target functional areas to the projection points on the virtual target plane is a polygonal region (not considering the case of multiple points being collinear).

[0120] The centroid of the largest area enclosed by the lines connecting the centroids of each target functional area to the projection points on the virtual target plane is a relatively balanced distance from the centroids of each target functional area. When the microneedle is placed in this position, each target functional area can be well taken into account.

[0121] Step S3063b: Detect whether the product of the centroid offset relative distance and the cross-functional zone coefficient is greater than the preset offset distance threshold.

[0122] Centroid offset relative distance The product of the cross-functional zone coefficient ψ can be expressed as:

[0123] If yes, proceed to step S3064b; otherwise, proceed to step S3065b.

[0124] Step S3064b: Adjust at least one side edge of the second modified implanted three-dimensional region by translating it in a direction closer to the virtual central axis, and take the second modified implanted three-dimensional region with the largest volume that meets the preset conditions and has completed the side edge adjustment as the final implanted three-dimensional region.

[0125] Step S3065b: The second modified implanted three-dimensional region is used as the final implanted three-dimensional region.

[0126] The preset condition is: the relative distance of the centroid offset corresponding to the second corrected implanted three-dimensional region after the lateral edge adjustment is completed. Product with the cross-functional zone coefficient ψ Less than or equal to the preset offset distance threshold ε, which is expressed as The preset offset distance threshold is a value set in advance according to actual needs, for example, the preset offset distance threshold is 100um.

[0127] Based on the above formula The variant is: In other words, given a fixed preset offset distance threshold ε, the larger the cross-functional zone coefficient ψ is, the greater the relative distance of centroid offset required. The smaller the value, the less centroid O is needed. g The closer it is to the projection point G1.

[0128] In addition, after meeting the preset conditions, the second corrected implanted three-dimensional region with the largest volume after completing the side edge adjustment is selected as the final implanted three-dimensional region, which is also to ensure that the final implanted three-dimensional region is as large as possible.

[0129] Figure 5 A flowchart illustrating another intracranial microneedle implantation assistance method provided in this disclosure embodiment. (See flowchart for example.) Figure 5 As shown, the auxiliary method not only includes steps S1 to S3 in the previous embodiment, but also includes step S3a between steps S1 and S3; at the same time, step S1 includes steps S101 to S103 in the previous embodiment.

[0130] In some embodiments, before step S3, step S3a is further included.

[0131] Step S3a: Determine the implantation difficulty coefficient corresponding to the current microneedle implantation based on the location of each target functional area and the location of each sensitive area contained within each target functional area.

[0132] In some embodiments, step S3a includes steps S3a01 and S3a02.

[0133] Step S3a01: Determine the regional difficulty coefficient corresponding to each target functional area.

[0134] In step S3a01, for each target functional area, the regional difficulty coefficient corresponding to the target functional area is determined by the following steps S3a011 to S3a014.

[0135] Step S3a011: In each tomographic scan image, the cross-sectional percentage of the sensitive area corresponding to multiple different measurement positions of the target functional area at the first preset direction is obtained by using an equal-interval measurement method along the first preset direction.

[0136] The cross-sectional proportion of the sensitive area is equal to the ratio of the sum of the widths of all sensitive areas contained in the target functional area along the second preset direction at the corresponding measurement position to the width of the entire target functional area along the second preset direction at the corresponding measurement position, wherein the first preset direction intersects with the second preset direction.

[0137] Figure 6 This is a schematic diagram illustrating the cross-sectional proportion of the sensitive area corresponding to multiple different measurement locations in a tomographic image for obtaining a target functional region in an embodiment of this disclosure. For example... Figure 6 As shown, as an example, the first preset direction Y is Figure 6 The vertical direction in the middle, the second preset direction X is Figure 6 The horizontal direction. In the first preset direction Y, each equal interval △Z serves as a lateral measurement position. Figure 6 Four measurement positions are illustrated in the example. Taking the cross-sectional percentage of the sensitive area corresponding to measurement position 2 as an example, the cross-sectional percentage of the sensitive area corresponding to measurement position 2 is equal to the ratio of the sum of the widths of the two sensitive areas along the second preset direction X at measurement position 2, w1+w2, to the width w0 of the entire target functional area along the second preset direction at measurement position 2, i.e., (w1+w2) / w0.

[0138] Based on the above principle, the cross-sectional percentage of the sensitive area corresponding to the target functional area at four different measurement locations in a tomographic image can be calculated.

[0139] Therefore, through the above step S3a01, the cross-sectional proportion of the sensitive area corresponding to the target functional area at multiple different measurement positions in each tomographic scan image can be calculated.

[0140] Step S3a012: Select the largest cross-sectional percentage of sensitive areas from all the cross-sectional percentages of sensitive areas corresponding to the target functional area, and use it as the first difficulty coefficient corresponding to the target functional area.

[0141] Step S3a013: Based on the three-dimensional position information of the target functional area in the three-dimensional reconstruction model and the three-dimensional position information of all sensitive areas contained in the target functional area in the three-dimensional reconstruction model, determine the second difficulty level coefficient corresponding to the target functional area.

[0142] The second difficulty coefficient is equal to the ratio of the sum of the volumes of all sensitive areas contained in the corresponding target functional area within the 3D reconstruction model to the volume of the target functional area within the 3D reconstruction model.

[0143] Step S3a014: Determine the regional difficulty coefficient corresponding to the target functional area based on the first difficulty coefficient and the second difficulty coefficient.

[0144] The regional difficulty coefficient corresponding to the target functional area is equal to the product of the first difficulty coefficient and the second difficulty coefficient corresponding to the target functional area.

[0145] Of course, in other embodiments, the first difficulty coefficient or the second difficulty coefficient corresponding to the target functional area can be directly used as the area difficulty coefficient corresponding to the target functional area.

[0146] Step S3a02: Determine the implantation difficulty coefficient corresponding to the current microneedle implantation based on the regional difficulty coefficient corresponding to each target functional area.

[0147] Among them, the implantation difficulty coefficient corresponding to the current microneedle implantation is the maximum value among the regional difficulty coefficients corresponding to all target functional areas.

[0148] Figure 7 A flowchart illustrating yet another intracranial microneedle implantation assistance method provided in this disclosure embodiment. (See flowchart for example.) Figure 7 As shown, this auxiliary method not only includes steps S1 to S3 in the previous embodiments, but also includes step S4 after step S3.

[0149] Step S4: Based on the final implantation 3D region and the target microneedle type of the current microneedle implantation obtained in advance, control the microneedle clamping module to select the target microneedle type from the microneedle platform and ensure that the microneedle size meets the requirements for placement in the final implantation 3D region.

[0150] In this disclosure, a microneedle stage holds multiple microneedles (which can be of different types and sizes). Microneedle types include, but are not limited to, single-stem microneedles, multi-stem microneedles, and array microneedles. Generally, the same type of position can have multiple different sizes.

[0151] In this disclosure, a pre-trained microneedle detection model can be used to identify the microneedle type of the microneedles placed on the microneedle stage and obtain the size information of each microneedle; then, the target microneedles with the microneedle type being the target microneedle type and the microneedle size being able to be placed in the final implantation three-dimensional area can be selected (the ability of a microneedle to be placed in the final implantation three-dimensional area can be detected by simulation).

[0152] The above step S4 enables automatic selection of microneedles; the microneedle clamping module can use negative pressure to clamp the selected microneedles.

[0153] In some embodiments, step S3 may be followed by step S5.

[0154] Step S5: During the implantation process of implanting the target microneedle into the target object, the imaging module captures images of the target microneedle and the target object's brain in real time as images of the implantation process.

[0155] The imaging module can be a visible light imaging module or an X-ray imaging model.

[0156] In some embodiments, at least one of steps S6 to S8 may be included after step S5.

[0157] Step S6: Using the image portion of the target object's brain in the implantation process image, perform image registration between the implantation process image and the target object's three-dimensional brain reconstruction model, and map the target microneedle into the three-dimensional brain reconstruction model. Detect the actual implantation direction corresponding to the target microneedle in the three-dimensional brain reconstruction model, and determine whether the angle between the actual implantation direction and the extension direction of the lateral edge of the final implanted three-dimensional area is greater than a preset angle threshold. When it is determined that the angle between the actual implantation direction and the extension direction of the lateral edge of the final implanted three-dimensional area is greater than the preset angle threshold, generate a first warning message to indicate that the implantation direction has deviated.

[0158] Step S6 above can effectively detect the actual implantation direction during the implantation process and provide effective reminders when the actual implantation direction deviates.

[0159] Step S7: Obtain the implantation speed of the target microneedle based on the two selected implantation process images, and determine whether the implantation speed is greater than a preset speed threshold. When it is determined that the implantation speed is greater than the preset speed threshold, generate a second reminder message to indicate that the implantation speed is too fast. The implantation speed is equal to the difference between the length of the target microneedle outside the target brain in the first implantation process image and the length of the target microneedle outside the target brain in the second implantation process image, divided by the difference in the shooting time of the two implantation process images.

[0160] Step S7 above can effectively detect the implantation speed during the implantation process and provide effective reminders when the implantation speed is too fast.

[0161] Step S8: Obtain the length of the target microneedle outside the target brain in the current frame implantation process image, calculate the ratio of the length of the target microneedle outside the target brain to the total length of the target microneedle as the remaining implantation progress, determine whether the remaining implantation progress is less than a preset progress threshold, and generate a third reminder message to indicate that the implantation depth is relatively deep when it is determined that the remaining implantation progress is less than the preset progress threshold (e.g., 15%), and generate a fourth reminder message to indicate that the microneedle has been completely implanted when the remaining implantation progress value is 0.

[0162] Step S8 above can effectively detect the implantation progress during the implantation process and provide corresponding reminders based on the implantation progress.

[0163] In some embodiments, the auxiliary method further includes step S9.

[0164] Step S9: During the implantation process of implanting the target microneedle into the target object, record and store the actual implantation direction, implantation speed and / or remaining implantation progress at different moments in the implantation process.

[0165] It should be noted that the technical solution disclosed herein does not limit the execution order of steps S6 to S9.

[0166] Based on the same inventive concept, this disclosure also provides an intracranial microneedle implantation assistance system. Figure 8 This is a structural block diagram of an intracranial microneedle implantation assistance system provided in an embodiment of this disclosure. Figure 8 As shown, the intracranial microneedle implantation assistance system can be used to implement the intracranial microneedle implantation assistance method provided in the previous embodiment. The intracranial microneedle implantation assistance system includes: a detection module, a determination module, and an adjustment module.

[0167] The detection module is configured to determine the location of each target functional area corresponding to the current microneedle implantation and the location of each sensitive area contained within each target functional area within the three-dimensional reconstruction model of the target object's brain.

[0168] The module is configured to determine a pre-implanted three-dimensional area within the target three-dimensional area composed of all target functional areas. The pre-implanted three-dimensional area is a quadrangular prism with the side edges extending in a preset implantation direction corresponding to the current microneedle implantation.

[0169] The adjustment module is configured to adjust the position of at least one face and / or at least one side edge of the pre-implanted 3D region by translating it in a direction closer to the centroid of the pre-implanted 3D region, so as to obtain the final implanted 3D region. The final implanted 3D region does not overlap with any of the sensitive regions.

[0170] For a detailed description of each of the above functional modules, please refer to the content in the previous embodiments, which will not be repeated here.

[0171] Based on the same inventive concept, this disclosure also provides an electronic device. Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Figure 9 As shown, this disclosure provides an electronic device including: one or more processors 101, a memory 102, and one or more I / O interfaces 103. The memory 102 stores one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement any of the intracranial microneedle implantation assistance methods described in the above embodiments; the one or more I / O interfaces 103 are connected between the processor and the memory, configured to enable information interaction between the processor and the memory.

[0172] The processor 101 is a device with data processing capabilities, including but not limited to a central processing unit (CPU); the memory 102 is a device with data storage capabilities, including but not limited to random access memory (RAM, more specifically SDRAM, DDR, etc.), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), and flash memory (FLASH); the I / O interface (read / write interface) 103 is connected between the processor 101 and the memory 102, and can realize information interaction between the processor 101 and the memory 102, including but not limited to a data bus (Bus).

[0173] In some embodiments, the processor 101, memory 102, and I / O interface 103 are interconnected via bus 104, and thus connected to other components of the computing device.

[0174] In some embodiments, the one or more processors 101 include a field-programmable gate array.

[0175] According to embodiments of this disclosure, a computer-readable medium is also provided. This computer-readable medium stores a computer program, which, when executed by a processor, implements the steps of any of the intracranial microneedle implantation assistance methods described in the above embodiments.

[0176] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a machine-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication component, and / or installed from a removable medium. When the computer program is executed by a central processing unit (CPU), it performs the functions defined above in the system of this disclosure.

[0177] It should be noted that the computer-readable medium disclosed herein may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying 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. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0178] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0179] The circuits or sub-circuits described in the embodiments of this disclosure can be implemented in software or hardware. The described circuits or sub-circuits can also be housed in a processor; for example, it can be described as: a processor including: a receiving circuit and a processing circuit, the processing module including a writing sub-circuit and a reading sub-circuit. The names of these circuits or sub-circuits do not necessarily constitute a limitation on the circuit or sub-circuit itself; for example, a receiving circuit can also be described as "receiving video signals".

[0180] It is understood that the above embodiments are merely exemplary embodiments used to illustrate the principles of this disclosure, and this disclosure is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and substance of this disclosure, and these modifications and improvements are also considered to be within the scope of protection of this disclosure.

Claims

1. A method for assisting in intracranial microneedle implantation, characterized in that, include: Within the three-dimensional reconstruction model of the target brain, the locations of each target functional area corresponding to the current microneedle implantation and the locations of each sensitive area contained within each target functional area are determined. A pre-implanted three-dimensional region is determined within the target three-dimensional region composed of all the target functional areas. The pre-implanted three-dimensional region is shaped like a quadrangular prism and the extension direction of the side edges is a preset implantation direction corresponding to the current microneedle implantation. The position of at least one face and / or at least one side edge of the pre-implanted three-dimensional region is adjusted by translating it in a direction closer to the centroid of the pre-implanted three-dimensional region, so as to obtain the final implanted three-dimensional region, which does not overlap with any of the sensitive regions.

2. The method according to claim 1, characterized in that, The step of determining the pre-implanted three-dimensional region within the target three-dimensional region comprised of all the aforementioned target functional regions includes: Within the target three-dimensional region, a cuboid region with the largest volume that extends along the preset direction and surrounds the centroid of the target three-dimensional region is identified as the pre-implanted three-dimensional region.

3. The method according to claim 2, characterized in that, The pre-implanted three-dimensional region has four side edges, four long edges, and four wide edges. The extension directions of the side edges, the long edges, and the wide edges are each configured with corresponding preset distance constants. The step of adjusting the position of at least one face and / or at least one side edge of the pre-implanted three-dimensional region by translating it toward the centroid of the pre-implanted three-dimensional region includes: At least one face of the pre-implanted three-dimensional region is translated toward the centroid of the pre-implanted three-dimensional region to determine the largest cuboid region in the non-sensitive region of the target three-dimensional region, excluding the sensitive region, as the first corrected implanted three-dimensional region; Based on the implantation difficulty coefficient corresponding to the current microneedle implantation obtained in advance, the safety distance corresponding to each face of the first modified implantation three-dimensional area is calculated. The safety distance is equal to the preset distance constant configured in the normal direction of the corresponding face multiplied by the implantation difficulty coefficient. Each face of the first modified implanted three-dimensional region is taken as the face to be adjusted, and it is determined whether the minimum distance between the avoidance area composed of all the sensitive areas and the face to be adjusted is less than the safe distance corresponding to the face to be adjusted. If so, the surface to be adjusted is translated toward the centroid of the pre-implanted three-dimensional area until the minimum distance between the avoidance area and the surface to be adjusted is equal to the safe distance corresponding to the surface to be adjusted. If not, keep the surface to be adjusted unchanged; The first corrected implantation three-dimensional region after the safety distance adjustment is completed is used as the second corrected implantation three-dimensional region, and the final implantation three-dimensional region is obtained based on the second corrected implantation three-dimensional region.

4. The method according to claim 3, characterized in that, The steps for obtaining the final implanted three-dimensional region based on the second corrected implanted three-dimensional region include: In response to the fact that the number of target functional areas corresponding to the current microneedle implantation is 1, the second modified implantation three-dimensional area is taken as the final implantation three-dimensional area; Alternatively, in response to the fact that the number of target functional areas corresponding to the current microneedle implantation is greater than 1, the cross-functional area coefficient corresponding to the current microneedle implantation is determined. The cross-functional area coefficient is equal to the product of the square root of the number of target functional areas and the standard deviation of the distance between the centroid of each target functional area and the centroid of the second modified implantation three-dimensional area. Obtain the centroid offset relative distance corresponding to the second corrected implanted three-dimensional region. The centroid offset relative distance is the distance between the centroid of the largest region enclosed by the line connecting the projection points of the centroids of the target functional regions on the virtual target plane when the centroids of the second corrected implanted three-dimensional region and the centroids of each target functional region are projected along the extension direction of the side edge of the pre-implanted three-dimensional region to the virtual target plane, and the projection point of the centroid of the second corrected implanted three-dimensional region on the virtual target plane. The virtual target plane is a virtual plane perpendicular to the extension direction of the side edge of the pre-implanted three-dimensional region. Detect whether the product of the centroid offset relative distance and the cross-functional zone coefficient is greater than a preset offset distance threshold; If so, a translation method is adopted in the direction closer to the virtual central axis to adjust at least one side edge of the second corrected implanted three-dimensional region, and the second corrected implanted three-dimensional region that has completed side edge adjustment and meets the preset conditions and has the largest volume is taken as the final implanted three-dimensional region. The preset conditions are: the product of the centroid offset relative distance corresponding to the second corrected implanted three-dimensional region that has completed side edge adjustment and the cross-functional region coefficient is less than or equal to the preset offset distance threshold. If not, then the second modified implanted three-dimensional region will be used as the final implanted three-dimensional region.

5. The method according to claim 3, characterized in that, Before the step of adjusting the position of at least one surface and / or at least one side edge of the pre-implanted three-dimensional region by translating it in a direction closer to the centroid of the pre-implanted three-dimensional region to obtain the corrected implanted three-dimensional region, the method further includes: Based on the location of each target functional area and the location of each sensitive area contained within each target functional area, the implantation difficulty coefficient corresponding to the current microneedle implantation is determined.

6. The method according to claim 5, characterized in that, The steps of determining the location of each target functional area corresponding to the current microneedle implantation and the location of each sensitive area contained within each target functional area within a three-dimensional reconstruction model of the target object's brain include: Acquire a set of brain tomographic images of the target object, the set of brain tomographic images including tomographic images of the target object's brain at multiple different scanning layers; Target functional area detection and sensitive area detection are performed on each of the tomographic scan images to obtain the two-dimensional position information of each target functional area corresponding to the current microneedle implantation in each tomographic scan image, as well as the two-dimensional position information of the sensitive areas contained in each target functional area. Based on the brain tomographic image set and the target functional area detection results and sensitive area detection results of each tomographic image, a three-dimensional reconstruction is performed to obtain the brain three-dimensional reconstruction model, the three-dimensional position information of each target functional area in the three-dimensional reconstruction model, and the three-dimensional position information of the sensitive areas contained in each target functional area in the three-dimensional reconstruction model. The steps for determining the implantation difficulty coefficient corresponding to the current microneedle implantation, based on the location of each target functional area and the location of each sensitive area contained within each target functional area, include: Determine the regional difficulty coefficient corresponding to each of the target functional areas; Based on the regional difficulty coefficient corresponding to each of the target functional areas, the implantation difficulty coefficient corresponding to the current microneedle implantation is determined, and the implantation difficulty coefficient is the maximum value among all the regional difficulty coefficients corresponding to the target functional areas; The step of determining the regional difficulty coefficient corresponding to a target functional area includes: In each of the tomographic scan images, the cross-sectional proportion of the sensitive area corresponding to multiple different measurement positions of the target functional area at the first preset direction is obtained by using an equal-interval measurement method along the first preset direction. The cross-sectional proportion of the sensitive area is equal to the ratio of the sum of the widths of all the sensitive areas contained in the target functional area at the corresponding measurement positions along the second preset direction to the width of the entire target functional area at the corresponding measurement positions along the second preset direction. The first preset direction intersects with the second preset direction. Select the largest cross-sectional percentage of the sensitive area from all the cross-sectional percentages of the sensitive areas corresponding to the target functional area, and use it as the first difficulty coefficient corresponding to the target functional area; Based on the three-dimensional position information of the target functional area in the three-dimensional reconstruction model and the three-dimensional position information of all the sensitive areas contained in the target functional area in the three-dimensional reconstruction model, a second difficulty coefficient corresponding to the target functional area is determined. The second difficulty coefficient is equal to the ratio of the sum of the volumes of all the sensitive areas contained in the target functional area in the three-dimensional reconstruction model to the volume of the target functional area in the three-dimensional reconstruction model. The regional difficulty coefficient corresponding to the target functional area is determined based on the first difficulty coefficient and the second difficulty coefficient, and the implantation difficulty coefficient is equal to the product of the first difficulty coefficient and the second difficulty coefficient.

7. The method according to claim 1, characterized in that, After obtaining the final implanted three-dimensional region, the process also includes: Based on the final implantation three-dimensional region and the pre-acquired target microneedle type for the current microneedle implantation, the microneedle clamping module is controlled to select a target microneedle from the microneedle platform that is of the target microneedle type and whose size is sufficient to be placed within the final implantation three-dimensional region.

8. An intracranial microneedle implantation assist system, characterized in that, include: The detection module is configured to determine the location of each target functional area corresponding to the current microneedle implantation and the location of each sensitive area contained within each target functional area within the three-dimensional reconstruction model of the target object's brain; The determination module is configured to determine a pre-implanted three-dimensional area within the target three-dimensional area composed of all the target functional areas, wherein the shape of the pre-implanted three-dimensional area is a quadrangular prism and the extension direction of the side edges is a preset implantation direction corresponding to the current microneedle implantation. The adjustment module is configured to adjust the position of at least one face and / or at least one side edge of the pre-implanted three-dimensional region by translating it in a direction closer to the centroid of the pre-implanted three-dimensional region, so as to obtain the final implanted three-dimensional region, wherein the final implanted three-dimensional region does not overlap with any of the sensitive regions.

Images