基于端到端深度学习网络的皮肤病变初级形态分类

2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) Pub Date : 2019-02-01 DOI:10.1109/ICAIIC.2019.8668980

T. Polevaya, R. Ravodin, A. Filchenkov

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引用次数: 7

摘要

皮肤病变的自动诊断是一个高度关注的领域。识别皮肤病变的原始形态可能是自动诊断工具的第一步。我们提出了一种端到端的深度学习解决方案，用于对斑、结节、丘疹和斑块类型的原始形态学图像进行分类。实验结果表明，4个分类的准确率为0.775,3个分类的准确率为0.8167。

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Skin Lesion Primary Morphology Classification With End-To-End Deep Learning Network

Automatic diagnostics of skin lesions is an area of high interest. Identification of primary morphology in skin lesions could be a first step of an automatic diagnostics tool. We propose an end-to-end deep learning solution to the problem of classifying primary morphology images of types macule, nodule, papule and plaque. Experimental results show 0.775 accuracy on 4 classes and 0.8167 accuracy on 3 classes.

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2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

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