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

作　　者：王刚 孟宁[1,2] 朱进 李春杰[1,2] Wang Gang;Meng Ning;Zhu Jin;Li Chunjie(School of Software,University of Science and Technology of China,Suzhou 215000,Jiangsu,China;Suzhou Advanced Research Institute,University of Science and Technology of China,Suzhou 215000,Jiangsu,China;Department of Urology,Second Affiliated Hospital of Soochow University,Suzhou 215000,Jiangsu,China)

机构地区：[1]中国科学技术大学软件学院,江苏苏州215000 [2]中国科学技术大学苏州高等研究院,江苏苏州215000 [3]苏州大学附属第二医院泌尿外科,江苏苏州215000

出　　处：《计算机应用与软件》2025年第4期21-26,99,共7页Computer Applications and Software

基　　金：国家自然科学基金项目(81773221);苏州市科技计划项目(SS201857);苏州大学高校省级重点实验室开放课题项目(KJS1963)。

摘　　要：前列腺癌已经成为全球男性发病率仅次于肺癌的第二大癌症,其死亡率位居第五。设计前列腺癌智能辅助诊断系统具有重要临床意义。在仅有图像级标注数据集的情况下,存在利用卷积神经网络只对图像分类,但没有给出癌化区域。针对这种情况,采用以EfficientNet-B0为架构的卷积神经网络模型为基础分类模型,对图像分块并得到每块的类别,再通过聚类算法得到癌化区域。在Web前端上传病理图像,等处理完成后可以查看辅助诊断结果。实验结果表明,该系统癌化区域的精确率为76.61%,召回率为72.52%,能有效地得到大致区域,获得满意的辅助诊断效果。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 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]