Skin Cancer Segmentation On Dermoscopy Images Using Fuzzy C-Means Algorithm - Aldi, Febri; Sumijan (AI Society & STMIK Indonesia, 2024)
Millions of people around the world suffer from skin cancer, a common and sometimes fatal disease. Dermoscopy has become an effective diagnostic technique for skin cancer. Precise segmentation is essential for skin cancer diagnosis. Segmentation allows more precise analysis of dermoscopic images by defining the boundaries of the lesion and separating it from surrounding healthy tissue. Dermoscopy images served as a source of research data, and Fuzzy C-Means (FCM) segmentation techniques were used. FCM is a promising method and has received a lot of attention lately. FCM is able to distinguish the various components within the lesion and effectively separate the lesion from the surrounding area. As a result, the distribution of membership degree values of each pixel in the image for each cluster represents the segmentation results obtained through FCM. The FCM technique for segmenting dermoscopic images is expected to significantly improve the precision and effectiveness of skin cancer diagnosis.