Microneedle patch size determination method and system and medium

By acquiring three-dimensional image data of the body surface, calculating the principal curvature coefficient and the fit index, performing cluster analysis, and generating the microneedle patch base size, the problem of poor adhesion of microneedle patches on three-dimensional curved skin is solved, achieving precise adhesion and large-area coverage.

CN121999030AActive Publication Date: 2026-05-08NANTONG XINSHIYUAN BIOTECHNOLOGY CO LTD
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Patent Information

Application Number
CN202610459248.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-04-09
Publication Date
2026-05-08
Estimated Expiration
2046-04-09

AI Technical Summary

Technical Problem

Existing technologies cannot accurately assess the adhesion of microneedles to three-dimensional curved skin, leading to poor adhesion and potential problems such as wrinkles, curling, or detachment.

Method used

By acquiring three-dimensional image data of the target object's application site, preprocessing and segmentation are performed, local point cloud data is extracted for surface fitting, principal curvature coefficient and fit index are calculated, cluster analysis is performed, and the base size of the microneedle patch is generated.

Benefits of technology

It enables precise evaluation of the microneedle patch's fit on three-dimensional curved skin, reducing the risk of wrinkles and curling, ensuring good adhesion between the microneedle patch and the skin, and maximizing the effective treatment area.

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Abstract

The invention provides a microneedle patch size determination method and system and a medium, and relates to the technical field of microneedle patch size determination, and the method comprises the steps: obtaining body surface three-dimensional image data of a to-be-applied part, and segmenting the data into a plurality of sub-regions after preprocessing; performing image analysis on each sub-region, extracting local point cloud data, performing curved surface fitting, determining a main curvature coefficient of each sub-region, and further determining a fitting degree index of each sub-region; performing clustering analysis on all the sub-regions according to the fitness indexes, dividing the adjacent sub-regions of which the fitness indexes are located in the same preset interval into the same cluster, extracting local point cloud data of each cluster, performing fitting to generate a region boundary contour line, and incorporating the region boundary contour line into an initial microneedle patch contour line set; and screening and optimizing the initial microneedle patch contour line set to obtain candidate contour lines, smoothing the candidate contour lines to generate a target microneedle patch contour line, and determining an area enclosed by the target microneedle patch contour line as the substrate size of the microneedle patch.
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