CN-121999030-A - Microneedle patch size determining method, system and medium

CN121999030ACN 121999030 ACN121999030 ACN 121999030ACN-121999030-A

Abstract

The invention provides a method, a system and a medium for determining the size of a microneedle patch, which relate to the technical field of the size determination of the microneedle patch and comprise the steps of obtaining body surface three-dimensional image data of a part to be attached, dividing the body surface three-dimensional image data into a plurality of subareas after pretreatment, carrying out image analysis on each subarea, extracting local point cloud data, carrying out surface fitting, determining a main curvature coefficient of each subarea, further determining the attachment degree index of each subarea, carrying out cluster analysis on all subareas according to the attachment degree index, dividing the subareas which are adjacent and located in the same preset interval into the same cluster, extracting the local point cloud data of each cluster, fitting to generate a regional boundary contour line, incorporating the regional boundary contour line into an initial microneedle patch contour line set, screening and optimizing the initial microneedle patch contour line set to obtain candidate contour lines, carrying out smooth treatment on the candidate contour lines, generating a target microneedle patch contour line, and determining the enclosed region as the substrate size of the microneedle patch.

Inventors

ZENG JINSUI
YANG ZHOUJU
QIU ZIHAN

Assignees

南通新世元生物科技有限公司

Dates

Publication Date: 20260508
Application Date: 20260409

Claims (9)

1. The method for determining the size of the microneedle patch is characterized by comprising the following specific steps of: step 1, acquiring body surface three-dimensional image data of a part to be applied of a target object, preprocessing the body surface three-dimensional image data, dividing the preprocessed body surface three-dimensional image data into a plurality of subareas, wherein each subarea corresponds to a local surface unit of the part to be applied; Step 2, carrying out image analysis on each subarea, extracting local point cloud data corresponding to each subarea, carrying out surface fitting according to the local point cloud data, and determining a main curvature coefficient of each subarea, wherein the main curvature coefficient is used for representing the bending degree of a corresponding local surface unit; Step 3, carrying out cluster analysis on all subareas according to the laminating degree index of each subarea, dividing the subareas which are adjacent and have the laminating degree index within the same preset index interval into the same clusters to obtain a plurality of clusters; and 4, screening and optimizing the initial microneedle patch contour line set to obtain candidate contour lines, smoothing the candidate contour lines to generate target microneedle patch contour lines, and determining the area surrounded by the target microneedle patch contour lines as the substrate size of the microneedle patch.
2. The method for determining the size of the microneedle patch of claim 1, wherein the three-dimensional image data of the body surface is acquired by a three-dimensional scanning device, and the preprocessing comprises denoising and filtering the three-dimensional image data of the body surface to eliminate isolated noise points and smoothing to eliminate irregular protrusions on the surface; dividing the preprocessed body surface three-dimensional image data into a plurality of subareas, namely uniformly dividing the body surface three-dimensional image data into a plurality of subareas according to a preset grid size, wherein the size of each subarea is the same, and each subarea corresponds to a local surface unit of a part to be applied.
3. The method for determining the size of the microneedle patch according to claim 2, wherein the specific logic on which the image analysis is performed on each subregion and the local point cloud data corresponding to each subregion is extracted is as follows: the method comprises the steps of establishing a three-dimensional coordinate system, mapping each pixel point in three-dimensional image data of a body surface to a three-dimensional space, carrying out image pixel analysis on each sub-area, extracting image coordinates and depth information corresponding to all pixel points in the range of the sub-area, determining X-axis coordinates and Y-axis coordinates of each pixel point in the three-dimensional space according to the image coordinates, determining Z-axis coordinates of each pixel point in the three-dimensional space according to the depth information, forming three-dimensional space points corresponding to the pixel points by the X-axis coordinates, the Y-axis coordinates and the Z-axis coordinates together, forming local point cloud data corresponding to the sub-area by all the three-dimensional space points, and uniquely corresponding to one pixel point in the sub-area by each three-dimensional space point; searching the local point cloud data for the nearest point from the geometric center point of each subarea serving as the query point Three-dimensional space points to be searched The three-dimensional space points form a neighborhood point set corresponding to the sub-region, and the neighborhood point set is used for representing local surface morphology around the central point of the sub-region; Fitting a local quadric surface by using a least square method based on the neighborhood point set, wherein the local quadric surface is a quadratic polynomial function of local plane coordinates taking a center point of a sub-region as an origin, the function is composed of a quadratic term coefficient, a first order coefficient and a constant term, the local plane coordinates are obtained by transforming three-dimensional space coordinates of three-dimensional space points in the neighborhood point set through coordinates, and a function value of the quadratic polynomial function is a height value on the curved surface at a corresponding point position; calculating a first basic quantity and a second basic quantity of a curved surface of the subarea according to the local quadric parameter obtained by fitting, wherein the first basic quantity of the curved surface comprises 、、 For describing arc length and angle measure on a curved surface, the second basic quantity of the curved surface comprises 、、 The method is used for representing the bending degree of the curved surface in space; Obtaining a principal curvature coefficient of the subarea by solving a characteristic equation formed by the first basic quantity and the second basic quantity, wherein the characteristic equation is a unitary quadratic equation taking the principal curvature coefficient as an unknown number, and three coefficients of the equation are respectively obtained by combination operation of the first basic quantity and the second basic quantity; solving the unitary quadratic equation to obtain two roots, and taking the root with the largest absolute value as the principal curvature coefficient of the subarea.
4. A method for determining the size of a microneedle patch according to claim 3, wherein the fitting index of each subregion is determined according to the principal curvature coefficient, specifically, for each subregion, the principal curvature coefficient of the subregion is obtained, and the maximum value and the minimum value of the principal curvature coefficient in all subregions are obtained; the value range of the fit index is between 0 and 1, the larger the fit index is, the higher the fit degree of the microneedle patch at the subarea and the body surface is, and the smaller the fit index is, the lower the fit degree is.
5. The method for determining the size of the microneedle patch according to claim 1, wherein the clustering analysis is performed on all the subregions according to the fitness index of each subregion, specifically: S31, creating an empty cluster set, and initializing all sub-areas to be in an unaccessed state; s32, selecting one initial seed point as a current cluster from the unviewed subareas, marking the initial seed point as accessed, and taking the initial seed point as a current seed point; S33, searching sub-areas which are adjacent to the current seed point and are not accessed, judging whether the fitting degree index of each searched adjacent sub-area falls into a corresponding preset index interval, wherein the upper limit and the lower limit of the preset index interval are respectively the fitting degree index of the initial seed point in the current cluster, and adding a preset amplitude value and subtracting a preset amplitude value; S34, if the judgment result of one adjacent subarea is yes, marking the adjacent subarea as accessed, and dividing the adjacent subarea into current clusters, and simultaneously taking the adjacent subarea as a new current seed point, recursively and repeatedly executing the searching and judging process in S33 until a new adjacent subarea which meets the condition and is not accessed cannot be found from the current clusters; S35, storing the formed current clusters into a cluster set, returning to S32 until all the subareas are marked as accessed, thus obtaining a plurality of clusters formed by adjacent subareas with the attachment index in the same preset index interval, and calculating the attachment index average value of the subareas in each cluster to be used as the comprehensive attachment index of the cluster; And extracting edge points of the clusters by adopting a convex hull algorithm based on the whole point cloud data, performing curve fitting on the edge points to generate a region boundary contour line of the clusters as an initial microneedle patch contour line, and summarizing all the initial microneedle patch contour lines to construct an initial microneedle patch contour line set.
6. The method for determining a size of a microneedle patch of claim 5, wherein said initial set of microneedle patch contours is selected and optimized by: S41, traversing each initial microneedle patch contour line in an initial microneedle patch contour line set, calculating the area of a surrounded area of any initial microneedle patch contour line, and taking the area as an area value of a corresponding initial microneedle patch contour line, wherein the area calculating method comprises the steps of projecting the initial microneedle patch contour line to a two-dimensional plane along the normal direction of a part to be applied to obtain a two-dimensional closed curve, calculating the area of the area surrounded by the two-dimensional closed curve by adopting a polygon area calculating formula, sequencing all initial microneedle patch contour lines according to the sequence of the comprehensive fit index from large to small, selecting the initial microneedle patch contour line sequenced at the first as a current preferred object, and executing the following steps: S42, judging whether the area value of the current preferred object is larger than or equal to a preset minimum effective area threshold value, if so, taking the current preferred object as a candidate contour line and ending the optimization flow, and if not, entering S43; S43, fusing objects by taking the current preferred object as a reference, traversing other adjacent initial microneedle patch contour lines according to the sequence from large to small of area values, and judging whether each traversed initial microneedle patch contour line and the reference fusion object meet the fusion condition or not, wherein the fusion condition comprises that the traversed initial microneedle patch contour line and the clusters corresponding to the reference fusion object are adjacent in space positions, and the absolute difference value of the comprehensive laminating degree indexes of the traversed initial microneedle patch contour line and the reference fusion object is smaller than a preset difference threshold; If the traversed initial microneedle patch contour line meets the fusion condition, merging the corresponding cluster into the cluster corresponding to the reference fusion object to obtain a fusion cluster, calculating the comprehensive fit index of the fusion cluster, and generating the region boundary contour line of the fusion cluster to serve as the updated current preferred object; S44, returning to S42 until the optimization flow is finished or the fusion cannot be continued, selecting the initial microneedle patch contour lines ordered in the next position as the current preferred object when the fusion cannot be continued, and returning to S42 until the optimization flow is finished or all the initial microneedle patch contour lines are used as the current preferred object; If all the initial microneedle patch contours have been treated as currently preferred objects, but the candidate contours have not yet been determined, then other locations of the target object are alternatively treated as the site to be applied.
7. The method for determining the size of a microneedle patch of claim 6, wherein the method comprises performing cubic B-spline curve fitting on the discrete point sequence on the candidate contour line, and taking the cubic B-spline curve generated after fitting as a target microneedle patch contour line; And extracting all image pixel areas surrounded by the contour line of the target microneedle patch in the three-dimensional image data of the body surface, and determining the surface area corresponding to the image pixel areas in the three-dimensional space as the substrate size of the part of the microneedle patch to be applied.
8. A microneedle patch sizing system for performing a method of microneedle patch sizing according to any one of claims 1 to 7, comprising: the image acquisition and segmentation module is used for acquiring body surface three-dimensional image data of a part to be applied of a target object, preprocessing the body surface three-dimensional image data, segmenting the preprocessed body surface three-dimensional image data into a plurality of subareas, and each subarea corresponds to a local surface unit of the part to be applied; The curvature and fitting degree calculation module is used for carrying out image analysis on each subarea, extracting local point cloud data corresponding to each subarea, carrying out surface fitting according to the local point cloud data, and determining a main curvature coefficient of each subarea, wherein the main curvature coefficient is used for representing the bending degree of a corresponding local surface unit; The clustering module is used for carrying out clustering analysis on all the subareas according to the laminating degree index of each subarea, dividing the subareas which are adjacent and have the laminating degree index within the same preset index interval into the same clusters to obtain a plurality of clusters; the size determining module is used for screening and optimizing the initial microneedle patch contour line set to obtain candidate contour lines, smoothing the candidate contour lines to generate target microneedle patch contour lines, and determining the area surrounded by the target microneedle patch contour lines as the substrate size of the microneedle patch.
9. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements a method for determining the size of a microneedle patch according to any one of claims 1 to 7.

Description

Microneedle patch size determining method, system and medium Technical Field The invention relates to the technical field of microneedle patch size determination, in particular to a method, a system and a medium for determining the microneedle patch size. Background The microneedle patch is used as a novel transdermal drug delivery carrier, is composed of a substrate and a plurality of fine needle-shaped structures arranged on the substrate, can penetrate through skin cuticle to form a microchannel, realizes efficient transdermal delivery of medicines, and has wide application prospects in the fields of beauty skin care, vaccination, chronic disease treatment and the like. However, poor adhesion of the microneedle patch to the skin can cause that the microneedle cannot effectively penetrate the skin, the drug permeability is reduced, and even wrinkles, curls or drops are generated at the application part, so that how to determine the size of the microneedle patch according to the surface morphology of the skin of an individual so that the microneedle patch can be closely adhered to the part to be applied is a key problem to be solved in the design and application of the microneedle patch. In the prior art, a mask size determining method, a system, electronic equipment and a medium with a publication number of CN117765586A are used for determining the optimal clustering number by collecting face size data of a sample group, clustering the sample data into a plurality of clusters by adopting an elbow method, determining a plurality of groups of target face size data according to the clustering center points of the clusters, and further designing a plurality of mask sizes. For the microneedle patch, the part to be applied is not an ideal plane, but a three-dimensional curved surface with complex curvature change, and the actual fitting condition of the microneedle patch and the skin is difficult to accurately reflect only by means of the two-dimensional size characteristics, so that the problem that the determined size of the microneedle patch still can cause poor fitting in actual use is solved. The above information disclosed in the background section is only for enhancement of understanding of the background of the disclosure and therefore it may include information that does not form the prior art that is already known to a person of ordinary skill in the art. Disclosure of Invention The invention aims to provide a method, a system and a medium for determining the size of a microneedle patch, so as to solve the problems in the background art. In order to achieve the above purpose, the present invention provides the following technical solutions: A method and a system for determining the size of a microneedle patch specifically comprise the following steps: step 1, acquiring body surface three-dimensional image data of a part to be applied of a target object, preprocessing the body surface three-dimensional image data, dividing the preprocessed body surface three-dimensional image data into a plurality of subareas, wherein each subarea corresponds to a local surface unit of the part to be applied; Step 2, carrying out image analysis on each subarea, extracting local point cloud data corresponding to each subarea, carrying out surface fitting according to the local point cloud data, and determining a main curvature coefficient of each subarea, wherein the main curvature coefficient is used for representing the bending degree of a corresponding local surface unit; Step 3, carrying out cluster analysis on all subareas according to the laminating degree index of each subarea, dividing the subareas which are adjacent and have the laminating degree index within the same preset index interval into the same clusters to obtain a plurality of clusters; and 4, screening and optimizing the initial microneedle patch contour line set to obtain candidate contour lines, smoothing the candidate contour lines to generate target microneedle patch contour lines, and determining the area surrounded by the target microneedle patch contour lines as the substrate size of the microneedle patch. The preprocessing comprises denoising and filtering the body surface three-dimensional image data to eliminate isolated noise points and smoothing to eliminate irregular protrusions on the surface; dividing the preprocessed body surface three-dimensional image data into a plurality of subareas, namely uniformly dividing the body surface three-dimensional image data into a plurality of subareas according to a preset grid size, wherein the size of each subarea is the same, and each subarea corresponds to a local surface unit of a part to be applied. Further, image analysis is carried out on each subarea, and local point cloud data corresponding to each subarea is extracted, wherein the specific logic is as follows: the method comprises the steps of establishing a three-dimensional coordinate system, mapping each pixel point in three-dimensiona