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皮肤镜图像分析:概述与未来方向。

Dermoscopy Image Analysis: Overview and Future Directions.

出版信息

IEEE J Biomed Health Inform. 2019 Mar;23(2):474-478. doi: 10.1109/JBHI.2019.2895803. Epub 2019 Jan 28.

Abstract

Dermoscopy is a non-invasive skin imaging technique that permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. While studies on the automated analysis of dermoscopy images date back to the late 1990s, because of various factors (lack of publicly available datasets, open-source software, computational power, etc.), the field progressed rather slowly in its first two decades. With the release of a large public dataset by the International Skin Imaging Collaboration in 2016, development of open-source software for convolutional neural networks, and the availability of inexpensive graphics processing units, dermoscopy image analysis has recently become a very active research field. In this paper, we present a brief overview of this exciting subfield of medical image analysis, primarily focusing on three aspects of it, namely, segmentation, feature extraction, and classification. We then provide future directions for researchers.

摘要

皮肤镜检查是一种非侵入性的皮肤成像技术,可使肉眼无法识别的色素性黑素细胞肿瘤的特征可视化。虽然对皮肤镜图像的自动分析研究可以追溯到 20 世纪 90 年代末,但由于各种因素(缺乏公开可用的数据集、开源软件、计算能力等),该领域在前 20 年进展相当缓慢。随着 2016 年国际皮肤成像协作组织发布了一个大型公共数据集、用于卷积神经网络的开源软件的出现以及廉价图形处理单元的可用性,皮肤镜图像分析最近成为一个非常活跃的研究领域。在本文中,我们简要介绍了医学图像分析这一令人兴奋的子领域,主要集中在三个方面,即分割、特征提取和分类。然后我们为研究人员提供了未来的方向。

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