计算机应用与软件2025，Vol.42Issue(4)：21-26,99,7.DOI:10.3969/j.issn.1000-386x.2025.04.004
基于深度学习的前列腺癌智能辅助诊断系统
INTELLIGENT AUXILIARY DIAGNOSIS SYSTEM FOR PROSTATE CANCER BASED ON DEEP LEARNING
摘要
Abstract
Prostate cancer ranks as the second most frequently diagnosed neoplasia and the fifth leading cause of mortality in male patients with cancer.It is of great clinical significance to design an image-assisted diagnosis system for prostate pathological section.In the case of only image-level annotation data set,convolutional neural network(CNN)is used to classify only images,but no cancerous regions are given.In view of this situation,the CNN model with efficientnet-B0 architecture was used as the basic classification model,the image was divided into patches and the categories of each patch were obtained,and the cancerous regions were obtained by clustering algorithm.Pathological images were uploaded on the Web front end,and auxiliary diagnosis results were viewed after the processing was completed.Experimental results show that the precision of the system is 76.61％,and the recall rate is 72.52％,which can effectively obtain the general area and obtain satisfactory auxiliary diagnosis effect.关键词
前列腺病理切片图像/卷积神经网络/图像分块/Web前端Key words
Image of pathological section of prostate/CNN/Image patch/Web front end分类
计算机与自动化引用本文复制引用
王刚,孟宁,朱进,李春杰..基于深度学习的前列腺癌智能辅助诊断系统[J].计算机应用与软件,2025,42(4):21-26,99,7.基金项目
国家自然科学基金项目(81773221) （81773221）
苏州市科技计划项目(SS201857) （SS201857）
苏州大学高校省级重点实验室开放课题项目(KJS1963). （KJS1963）
