Detection of pigment network in dermoscopy images using supervised machine learning and structural analysis

被引：50

作者：

Garcia Arroyo, Jose Luis ^{[1
]}

Garcia Zapirain, Begona ^{[1
]}

机构：

[1] Univ Deusto, Deustotech LIFE Unit eVIDA, Bilbao 48007, Spain

来源：

COMPUTERS IN BIOLOGY AND MEDICINE | 2014年 / 44卷

关键词：

Melanoma; Machine learning; Pigment network; Structural analysis; Reticular pattern; BLUE-WHITE VEIL; SKIN-LESIONS; ABCD RULE; EPILUMINESCENCE MICROSCOPY; PATTERN-RECOGNITION; MELANOMA DIAGNOSIS; SYSTEM; DERMATOSCOPY; CLASSIFICATION; FEATURES;

D O I：

10.1016/j.compbiomed.2013.11.002

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

By means of this study, a detection algorithm for the "pigment network" in dermoscopic images is presented, one of the most relevant indicators in the diagnosis of melanoma. The design of the algorithm consists of two blocks. In the first one, a machine learning process is carried out, allowing the generation of a set of rules which, when applied over the image, permit the construction of a mask with the pixels candidates to be part of the pigment network. In the second block, an analysis of the structures over this mask is carried out, searching for those corresponding to the pigment network and making the diagnosis, whether it has pigment network or not, and also generating the mask corresponding to this pattern, if any. The method was tested against a database of 220 images, obtaining 86% sensitivity and 81.67% specificity, which proves the reliability of the algorithm. (C) 2013 The Authors. Published by Elsevier Ltd. All rights reserved.

引用

页码：144 / 157

页数：14

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