光学精密工程2024，Vol.32Issue(24)：3644-3657,14.DOI:10.37188/OPE.20243224.3644
多尺度与三维交互特征优化的皮肤镜图像分类
Dermoscopic image classification based on multi-scale and three-dimensional interaction feature optimization
摘要
Abstract
Early diagnosis of skin cancer is crucial for improving patient outcomes and alleviating the bur-den on the healthcare system.However,the process of feature extraction in skin cancer image classifica-tion often results in information loss and challenges in simultaneously identifying independent types of fea-tures in the images.MTIFNet was proposed,which was a network that integrates three-dimensional spa-tial attention with information fusion.Initially,the network employed a multi-scale spatial adaptive mod-ule to extract both global and local contextual information from images during training.This module en-hanced the connection between blurred pixels around lesions and the relationship in pixels at different scales.Subsequently,a three-dimensional interaction feature optimization module was introduced to facili-tate connections across different dimensions,enabling the exchange and integration of information.Final-ly,cross-entropy loss was used to measure the difference between the predicted probability distribution and the true class distribution to optimize the accuracy of the model.The experimental results based on the ISIC 2018 and ISIC 2017 datasets indicate that the network has improved accuracy,precision,recall,and specificity to 94.32%,91.61%,93.00%,98.39%and 98.57%,98.20%,98.47%,99.13%,respec-tively.Compared to currently popular classification networks such as ResNeSt,ConvNext,and Fcanet,MTIFNet demonstrates superior capabilities in feature extraction and interaction,thereby assisting health-care professionals in making more precise diagnostic and treatment decisions.关键词
皮肤癌/图像分类/多尺度/空间自适应/三维交互Key words
skin cancer/image classification/multi-scale/spatial adaptation/three-dimensional interaction分类
信息技术与安全科学引用本文复制引用
王迪,吕晓琪,李菁..多尺度与三维交互特征优化的皮肤镜图像分类[J].光学精密工程,2024,32(24):3644-3657,14.基金项目
国家自然科学基金项目(No.61771266) （No.61771266）
