Abstract

Skin cancer is one of the most common and devastating forms of cancer. It is estimated that one out of every five individuals will develop skin cancer at some point in their lifetime. Early detection and treatment are essential for successful outcomes, and thus, developing automated and accurate detection methods for skin tumors is of great interest. In this paper, a bio-imaging based deep learning algorithm, have made it possible to accurately detect and analyze skin tumor diseases. This algorithm use complex neural network architectures to automatically identify and classify skin lesions from medical images. These methods can significantly help reduce the workload of dermatologists and improve the accuracy and speed of skin cancer detection. This study reviews the current research on automated skin tumor detection and analysis using deep learning algorithms, and presents some of the most promising directions for further investigation.

Authors

J. Seetha¹, D. Nagaraju², T. Kuntavai³, K. Gurnadha Gupta⁴
Panimalar Engineering College, India¹, Sri Venkatesa Perumal College of Engineering and Technology, India², Adhi Parasakthi Engineering College, India³, Koneru Lakshmaiah Education Foundation, India, India ⁴

Keywords

Skin Cancer, Early Detection, Treatment, Bio-Imaging, Deep Learning, Accuracy