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

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 ave

SUBMITTER: Lee H 

PROVIDER: S-EPMC10490539 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature