Deep Learning-Based Evaluation of Ultrasound Images for Benign Skin Tumors

Author:

Lee Hyunwoo1,Lee Yerin2,Jung Seung-Won3,Lee Solam3,Oh Byungho4,Yang Sejung2ORCID

Affiliation:

1. Department of Biomedical Engineering, Yonsei University, Wonju 26493, Republic of Korea

2. Department of Precision Medicine, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of Korea

3. Department of Dermatology, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of Korea

4. Department of Dermatology, Cutaneous Biology Research Institute, Yonsei University College of Medicine, Seoul 03722, Republic of Korea

Abstract

In this study, a combined convolutional neural network for the diagnosis of three benign skin tumors was designed, and its effectiveness was verified through quantitative and statistical analysis. To this end, 698 sonographic images were taken and diagnosed at the Department of Dermatology at Severance Hospital in Seoul, Korea, between 10 November 2017 and 17 January 2020. Through an empirical process, a convolutional neural network combining two structures, which consist of a residual structure and an attention-gated structure, was designed. Five-fold cross-validation was applied, and the train set for each fold was augmented by the Fast AutoAugment technique. As a result of training, for three benign skin tumors, an average accuracy of 95.87%, an average sensitivity of 90.10%, and an average specificity of 96.23% were derived. Also, through statistical analysis using a class activation map and physicians’ findings, it was found that the judgment criteria of physicians and the trained combined convolutional neural network were similar. This study suggests that the model designed and trained in this study can be a diagnostic aid to assist physicians and enable more efficient and accurate diagnoses.

Funder

Ministry of Education

Korean government

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

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