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Acral melanoma detection using a convolutional neural network for dermoscopy images

Title
Acral melanoma detection using a convolutional neural network for dermoscopy images
Authors
Yu, ChankiYang, SejungKim, WonohJung, JinwoongChung, Kee-YangLee, Sang WookOh, Byungho
Ewha Authors
이상욱
SCOPUS Author ID
이상욱scopus
Issue Date
2018
Journal Title
PLOS ONE
ISSN
1932-6203JCR Link
Citation
PLOS ONE vol. 13, no. 3
Publisher
PUBLIC LIBRARY SCIENCE
Indexed
SCIE; SCOPUS WOS scopus
Document Type
Article
Abstract
Background/Purpose Acral melanoma is the most common type of melanoma in Asians, and usually results in a poor prognosis due to late diagnosis. We applied a convolutional neural network to dermoscopy images of acral melanoma and benign nevi on the hands and feet and evaluated its usefulness for the early diagnosis of these conditions. Methods A total of 724 dermoscopy images comprising acral melanoma (350 images from 81 patients) and benign nevi (374 images from 194 patients), and confirmed by histopathological examination, were analyzed in this study. To perform the 2-fold cross validation, we split them into two mutually exclusive subsets: half of the total image dataset was selected for training and the rest for testing, and we calculated the accuracy of diagnosis comparing it with the dermatologist's and non-expert's evaluation. Results The accuracy (percentage of true positive and true negative from all images) of the convolutional neural network was 83.51% and 80.23%, which was higher than the non-expert's evaluation (67.84%, 62.71%) and close to that of the expert (81.08%, 81.64%). Moreover, the convolutional neural network showed area-under-the-curve values like 0.8, 0.84 and Youden's index like 0.6795, 0.6073, which were similar score with the expert. Conclusion Although further data analysis is necessary to improve their accuracy, convolutional neural networks would be helpful to detect acral melanoma from dermoscopy images of the hands and feet.
DOI
10.1371/journal.pone.0193321
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자연과학대학 > 물리학전공 > Journal papers
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