Automated Skin Cancer Detection: Where We Are and The Way to The Future

被引：36
作者：
Goceri, Evgin [1 ]
机构：
[1] Akdeniz Univ, Dept Biomed Engn, Antalya, Turkey
来源：
2021 44TH INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS AND SIGNAL PROCESSING (TSP) | 2021年
关键词：
classification; deep learning; lesion detection; skin lesion; skin cancer; DERMOSCOPY IMAGES; SEGMENTATION; LESIONS;
D O I：
10.1109/TSP52935.2021.9522605
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The most common and dreadful kinds of skin diseases is skin cancer. It can be caused by several factors such as prolonged exposure to sunlight, genetic defects and environmental factors. There are different kinds of skin cancer and the patients are usually not aware of recognizing the growth of skin lesions in the initial stage. For example, melanoma, which is a malignant lesion and one of the deadliest kinds. Skin cancer can be cured when it is detected early. Therefore, timely and accurate detection and treatment of the disease has a crucial role in the patients' survival. This paper aims to present an analysis of recent applications proposed for automated detection of skin cancer and future potentials to assist the investigators in developing efficient methods to achieve accurate, objective and early detection of the disease.
引用
收藏
页码：48 / 51
页数：4
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