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http://dx.doi.org/10.17662/ksdim.2018.14.4.069

A Computer Aided Diagnosis Algorithm for Classification of Malignant Melanoma based on Deep Learning  

Lim, Sangheon (계명대학교 의용공학과)
Lee, Myungsuk (계명대학교 타불라라사칼리지)
Publication Information
Journal of Korea Society of Digital Industry and Information Management / v.14, no.4, 2018 , pp. 69-77 More about this Journal
Abstract
The malignant melanoma accounts for about 1 to 3% of the total malignant tumor in the West, especially in the US, it is a disease that causes more than 9,000 deaths each year. Generally, skin lesions are difficult to detect the features through photography. In this paper, we propose a computer-aided diagnosis algorithm based on deep learning for classification of malignant melanoma and benign skin tumor in RGB channel skin images. The proposed deep learning model configures the tumor lesion segmentation model and a classification model of malignant melanoma. First, U-Net was used to segment a skin lesion area in the dermoscopic image. We could implement algorithms to classify malignant melanoma and benign tumor using skin lesion image and results of expert's labeling in ResNet. The U-Net model obtained a dice similarity coefficient of 83.45% compared with results of expert's labeling. The classification accuracy of malignant melanoma obtained the 83.06%. As the result, it is expected that the proposed artificial intelligence algorithm will utilize as a computer-aided diagnosis algorithm and help to detect malignant melanoma at an early stage.
Keywords
Deep Learning; Machine Learning; Malignant Melanoma; Convolutional Neural Network; Computer Aided Diagnosis;
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Times Cited By KSCI : 2  (Citation Analysis)
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