深度学习技术在皮肤影像自动分类中的应用

Application of Deep Learning Technology in Automatic Classification of Skin Images

以“胎儿超声图像”为例,将深度学习技术与皮肤影像自动分类进行充分结合。针对皮肤影像自动分类原理,从CNN原理介绍、网络模型设计、数据预处理及增强、迁移学习策略、模型训练与分类等方面入手,探讨了皮肤影像自动分类方法框架。从数据集及评价方法、模型定量化评价、模型可视化分析、与传统特征分类器对比试验等方面入手,探讨实验设置与结果。结果表明:深度学习技术具有非常高的应用价值和应用前景,不仅可以降低图像复杂预处理流程,还能避免对专业特征工程的过渡依赖,保证了皮肤影像视觉上的出色性能,为进一步提高皮肤疾病医疗诊断水平提供平台支持。

Taking the“fetal ultrasound image”as an example,the deep learning technology is fully combined with the automatic classification of skin images.Aiming to the principle of automatic classification of skin images,the framework of automatic classification of skin images is discussed,starting from the introduction of CNN principle,network model design,data pre-processing and enhancement,migration learning strategy,model training and classification.According to the principle of automatic classification of skin images,the framework of automatic classification of skin images is discussed,starting from the introduction of CNN principle,network model design,data pre-processing and enhancement,migration learning strategy,model training and classification.From the data set and evaluation method,model set quantitative evaluation,model visual analysis,and the traditional feature classifier comparison test and other aspects to explore the experimental setting and the results.The results show that deep learning technology has very high application value and application prospects,which can not only reduce the image complex preprocessing process,but also avoid the transition dependence on professional feature engineering,ensure the excellent visual performance of skin image,and provide platform support for further improve the medical diagnosis level of skin diseases.