Various Types of Skin Tumors Lesion Medical Imaging (STLMI) of Healthy and Unhealthy Moles a Review and Computational of: Segmentation, Classification, Methods and Algorithms

Abstract

Over recent decades, updates in the field of the imaging of skin tumor lesions and biomedical sensing at the side of its related clinical implementations have attracted the attention of scientists. The major aim is to develop an artificial bee colony algorithmic and other approaches to propose different types of skin cancer lesion medical imaging, utilizing medical images achieved through different imaging methods. The artificial bee colony is frequently used to get highly accurate analysis, which supports the early detection of that which poses a threat to life, and, this method can be a good area to examine for future research. We compared the achievement of many works that were developed specially to detect the skin tumours lesion of healthy and unhealthy nevi after the use of methods and algorithms to obtain good processing results and discussed the relevant conclusions. The paper presents develop various classification, segmentation, methods and algorithms to recognize benign and malignant nevi to help make an expert decision on dermatology. These methods would allow not just earlier detection of skin cancer cases, however, decreasing of the number of unnecessary of steps in image processing and costly process.