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一种具有类似皮肤科医生的肿瘤区域提取算法的基于互联网的改进型黑色素瘤筛查系统。

An improved Internet-based melanoma screening system with dermatologist-like tumor area extraction algorithm.

作者信息

Iyatomi Hitoshi, Oka Hiroshi, Celebi M Emre, Hashimoto Masahiro, Hagiwara Masafumi, Tanaka Masaru, Ogawa Koichi

机构信息

Department of Electronic Informatics, Hosei University Faculty of Engineering, Japan.

出版信息

Comput Med Imaging Graph. 2008 Oct;32(7):566-79. doi: 10.1016/j.compmedimag.2008.06.005. Epub 2008 Aug 15.

Abstract

In this paper, we present an Internet-based melanoma screening system. Our web server is accessible from all over the world and performs the following procedures when a remote user uploads a dermoscopy image: separates the tumor area from the surrounding skin using highly accurate dermatologist-like tumor area extraction algorithm, calculates a total of 428 features for the characterization of the tumor, classifies the tumor as melanoma or nevus using a neural network classifier, and presents the diagnosis. Our system achieves a sensitivity of 85.9% and a specificity of 86.0% on a set of 1258 dermoscopy images using cross-validation.

摘要

在本文中,我们展示了一个基于互联网的黑色素瘤筛查系统。我们的网络服务器全球可访问,当远程用户上传皮肤镜图像时执行以下程序:使用高度精确的类似皮肤科医生的肿瘤区域提取算法将肿瘤区域与周围皮肤分离,计算总共428个用于表征肿瘤的特征,使用神经网络分类器将肿瘤分类为黑色素瘤或痣,并给出诊断结果。我们的系统在一组1258张皮肤镜图像上使用交叉验证实现了85.9%的灵敏度和86.0%的特异性。

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