Skin Cancer Detection Using Artificial Intelligence

Abstract

Malignant melanoma is deadliest form of skin cancer but can be easily treated if newlinedetected in early stages. Due to increasing incidence of melanoma, researches in field newlineof autonomous melanoma detection are accelerated. Malignant melanoma is the most newlinesevere kind of skin cancer. It can grow anywhere on the body. Its exact cause is still newlineunclear but typically it s caused by ultraviolet exposure from sun or tanning beds. Its newlinedetection plays a very significant role because if detected early then it s curable, newlinebefore the spread has begun. It can be 95% recovered if it is early diagnosed. newlineMelanoma cases are rapidly increasing in Australia, New Zealand and Europe. newlineAustralia took highest place in the world with this deadly disease. Early diagnose of newlinemelanoma totally depends upon the accuracy and talent of practitioners. So automatic newlinedetection of melanoma is highly in demand as computer aided diagnosis methods give newlinegreat accuracy and they are non-invasive methods for the detection of melanoma. This newlinethesis investigates different methods for melanoma classification. In long run it will newlineoffer a source to test new and existing methodologies for skin cancer detection. newlineThe main objective of this thesis is to present detailed investigation for CAD in newlinemelanoma detection. Further thesis objective is to improve and build up relevant newlinesegmentation, feature extraction, feature selection and classification techniques that newlinecan cope up with the complexity of dermoscopic, clinical or histopathological images. newlineSeveral algorithms were developed during the path of thesis. These algorithms have newlinebeen used in skin cancer detection but they can be also used in other machine learning newlineapplications. newline newline