一种基于数据增强与模型优化的皮肤癌多分类建模方法
By using data augmentation and model optimization techniques, the gray-scale directional path and color trajectory of skin cancer images are extracted, solving the problems of insensitivity to image structure changes and inaccurate boundary detection in existing technologies, thereby improving the accuracy and efficiency of skin cancer diagnosis.
CN121837798BActive Publication Date: 2026-07-17HEFEI QIANSHOU MEDICAL TECH CO LTD
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HEFEI QIANSHOU MEDICAL TECH CO LTD
- Filing Date
- 2026-03-12
- Publication Date
- 2026-07-17
AI Technical Summary
Technical Problem
Existing multi-classification modeling methods for skin cancer have shortcomings such as insensitivity to changes in image structure, inaccurate detection of region boundaries, and imprecise state response analysis, resulting in low diagnostic accuracy and efficiency.
Method used
By extracting the grayscale path and color trajectory of skin cancer images, and combining data augmentation and model optimization techniques, the adjacency change trend and color interlacing segments are processed to generate skin cancer image enhancement results.
Benefits of technology
It improves the accuracy and efficiency of skin cancer diagnosis, enhances the distinguishability of image structures and the ability to locate abnormal areas, and improves classification performance and robustness.
✦ Generated by Eureka AI based on patent content.
Smart Images
Figure CN121837798B_ABST
Abstract
本发明涉及医学图像处理与人工智能技术领域，具体为一种基于数据增强与模型优化的皮肤癌多分类建模方法，获取像素序列执行通道比位移提取颜色主方向转灰度图，切片区域分离灰度范围读取邻接灰度序列处理边缘趋势抽取灰度方向向量，输出图块纹理方向灰度矩阵集合。本发明通过通道比例灰度位移建立颜色主方向与灰度响应关联，增强颜色与方向协同感知，通过切片灰度趋势采样强化图块方向区分，通过方向路径延展与不连续识别定位结构波动区域，通过颜色轨迹频率与方向映射形成灰度通断状态，通过纹理轮廓延展分析突出异常区域，并借助方向对齐与灰度层叠扩展结构差异覆盖范围。
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