ABSTRACT
Skin cancer is a widespread, global, and potentially deadly disease, which over the last three decades has afflicted more lives in the USA than all other forms of cancer combined. There have been a lot of promising recent works utilizing deep network architectures for developing automated skin lesion segmentation. Melanin is the pigment that discerns the color of human skin. The special cells produce melanin in the skin. If these cells are damaged or unhealthy, skin discoloration is visible. Skin pigment discoloration is a hazardous fact as a symptom of human skin cancer with a possibility of losing natural beauty. The extracted information of the skin discoloration can work as a guide to diagnosis the disease. The image analyzing results are visually examined by the skin specialist and are observed to be highly accurate. The visual results are presented in the project. This project will generate results faster than the traditional method, making this application an efficient and dependable system for dermatological cancer detection. Furthermore, this can also be used as a reliable real time teaching tool for medical students in the dermatology stream. This project is developed in matlab.
PROJECT OUTPUT
PROJECT DEMO VIDEO
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