通过计算机视觉检测皮肤癌“黑色素瘤”

2017 IEEE XXIV International Conference on Electronics, Electrical Engineering and Computing (INTERCON) Pub Date : 2017-08-01 DOI:10.1109/INTERCON.2017.8079674

Wilson F. Cueva, F. Muñoz, G. Vásquez, G. Delgado.

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引用次数: 22

摘要

在过去的几十年里，皮肤癌的发病率上升，成为一个公共卫生问题。技术的进步使得帮助黑色素瘤早期检测的应用程序得以发展。在此背景下，开发了一种图像处理方法来获得黑色素瘤的不对称性、边界、颜色和直径(ABCD)。用神经网络对不同种类的鼹鼠进行分类。结果，该算法在对200张图像进行分析后，获得了97.51%的性能。

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Detection of skin cancer ”Melanoma” through computer vision

In the last decades, skin cancer increased its incidence becoming a public health problem. Technological advances have allowed the development of applications that help the early detection of melanoma. In this context, an image processing was developed to obtain Asymmetry, Border, Color, and Diameter (ABCD of melanoma). Using neural networks to perform a classification of the different kinds of moles. As a result, this algorithm developed after an analysis of 200 images was obtained a performance of 97.51%.

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2017 IEEE XXIV International Conference on Electronics, Electrical Engineering and Computing (INTERCON)

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