Melanoma skin cancer segmentation with image processing techniques

Although melanoma is the least common skin cancer, it is the most dangerous type of skin cancer. On the other hand, if it is diagnosed in the early stages, the chance of success in its treatment is quite high. Dermoscopy is a non-invasive imaging technique for diagnosis. Considerable attention is currently paid to the development of computer-aided diagnostic systems to assist in the clinical evaluation of dermatologists. Image segmentation is a mechanism used to divide an image into multiple segments. It will make the image smooth and easy to evaluate. Segmentation also helps to find the region of interest in a particular image. The main goal is to make the image simpler and more expressive. In this thesis, dermoscopy images from Hospital Pedro Hispano (HPH) were used. Median filtering was applied to the images in order to reduce the noise. Melanoma skin cancer images were segmented by the Otsu thresholding method. A graphical user interface has been designed for this purpose. According to the results of the performance analysis, it was observed that the proposed method achieved the highest classification accuracy of 93% on the images in the database.