四川医学2024，Vol.45Issue(6)：638-645,8.DOI:10.16252/j.cnki.issn1004-0501-2024.06.013
基于高分辨率卷积神经网络的皮肤常见肿瘤智能诊断模型构建
Construction of Intelligent Diagnosis Model for Common Skin Tumors Based on High Resolution Convolutional Neural Network
摘要
Abstract
Objective To explore the application of high-resolution convolutional neural network(HRNetW32)model in the clinical diagnosis of common skin tumors.Methods Propose an intelligent diagnosis model for common skin tumors based on high-resolution feature extraction,uses the HRNetW32 model to realize the unified input of dermoscopic images of common skin tumors and automatically predict the diagnostic results of common skin tumor types.At the same time,the constructed model is compared with common convolutional neural network models such as VGG16,VGG19,and ResNet34.Results The accuracy of the HRNetW32 model in the training set and the validation set were 99.72%and 95.00%,respectively,and the loss function values were 0.15 and 0.21,respectively,indicating that the constructed model could accurately and efficiently extract the high-dimensional features of dermoscopic images of common skin tumors,and the HRNetW32 model showed better precision,recall,MicroF1 score,sensitivity,specificity,true rate and false positive rate than VGG16,VGG19 and ResNet34 models.Conclusion The HRNetW32 model can be used for the screening of common skin tumors,and has high diagnostic accuracy and high clinical diagnostic value.关键词
皮肤肿瘤诊断/图像识别/特征融合/高分辨率卷积神经网络Key words
skin tumor diagnosis/image recognition/feature fusion/high resolution convolutional neural network分类
临床医学引用本文复制引用
周兴雯,马春驰,王琳..基于高分辨率卷积神经网络的皮肤常见肿瘤智能诊断模型构建[J].四川医学,2024,45(6):638-645,8.基金项目
凉山州2021年度技术研究开发与推广应用项目(编号:21ZDYF0106) （编号:21ZDYF0106）
