期刊
COMPUTERS IN BIOLOGY AND MEDICINE
卷 44, 期 -, 页码 144-157出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compbiomed.2013.11.002
关键词
Melanoma; Machine learning; Pigment network; Structural analysis; Reticular pattern
类别
资金
- Basque Government Department of Education (eVIDA Certified Group) [IT579-13]
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.
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