Two segmentation methods for the diagnosis of malignant melanoma
Abstract
Automatic diagnosis of malignant melanoma highly depends on the segmentation methods used for the suspicious lesion. We suggest the parameter selection method (PSM) and maximum area method (MAM) for the segmentation of the lesion to be diagnosed. Herein, these segmentation methods are compared to a skin cancer expert’s segmentation and three other conventional algorithms. The diagnoses of malignant melanoma based on the two suggested, three conventional, and expert’s segmentation are compared with respect to sensitivity, specificity, and accuracy.
Copyright © 2021 Seungmin Park, Hyunju Lee, Kiwoon Kwon. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Cite this article
S. Park, H. Lee, K. Kwon, Two segmentation methods for the diagnosis of malignant melanoma, J. Math. Comput. Sci. 11 (2021), 3361–3376. https://doi.org/10.28919/jmcs/5650
BibTeX
@article{Park2021,
author = {Park, Seungmin and Lee, Hyunju and Kwon, Kiwoon},
title = {Two segmentation methods for the diagnosis of malignant melanoma},
journal = {J. Math. Comput. Sci.},
volume = {11},
year = {2021},
pages = {3361--3376},
doi = {10.28919/jmcs/5650}
}