Analysis of Malignant and Non-malignant Lesion Detection Techniques for Human Skin Image

Abstract

The early determination of skin sore illnesses is exceptionally challenging for individuals living in rustic regions because of inaccessibility of qualified dermatologists. In this situation, the dermatologists can analyze skin sore illnesses via cautiously looking high quality at anyplace. Further, the AI-based programmed analytic framework might help essential wellbeing experts for fast and precise detection of certain skin disorders. Consequently, there is a requirement of artificial intelligence-based medical image processing and examination of skin lesion images to enhancing their perceptibility characteristics. The use of image processing in biomedicine for diagnostic purposes is a non-invasive method. The potential for automatic image analysis approaches that offering quantifiable data on a lesion that can be utilized clinically and as a standalone early warning tool is pretty high. High quality digital photographs of melanoma skin lesions have been researched as a potential early skin cancer detection method without the need for skin biopsies. A strong artificial intelligence-based software application for skin lesion identification and detection will provide a better classification scheme and maybe enhance the automatic diagnosis of skin lesions. In this review article, we have analyzed and reviewed various malignant and non-malignant skin lesion detection techniques for human skin image.