Skin Cancer Detection Using Deep Learning—A Review

Author:

Naqvi Maryam1,Gilani Syed Qasim2,Syed Tehreem3,Marques Oge2,Kim Hee-Cheol1

Affiliation:

1. Institute of Digital Anti-Aging Healthcare, Inje University, Gimhae 50834, Republic of Korea

2. Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA

3. Department of Electrical Engineering and Computer Engineering, Technische Universität Dresden, 01069 Dresden, Germany

Abstract

Skin cancer is one the most dangerous types of cancer and is one of the primary causes of death worldwide. The number of deaths can be reduced if skin cancer is diagnosed early. Skin cancer is mostly diagnosed using visual inspection, which is less accurate. Deep-learning-based methods have been proposed to assist dermatologists in the early and accurate diagnosis of skin cancers. This survey reviewed the most recent research articles on skin cancer classification using deep learning methods. We also provided an overview of the most common deep-learning models and datasets used for skin cancer classification.

Funder

MSIT (Ministry of Science ICT), Korea

Publisher

MDPI AG

Subject

Clinical Biochemistry

Reference88 articles.

1. (2023, May 01). Skin Cancer. Available online: https://tinyurl.com/ptp97uzv.

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5. Automatic segmentation of dermoscopy images using saliency combined with Otsu threshold;Fan;Comput. Biol. Med.,2017

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