Feature extraction of epiluminescence microscopic images by iterative segmentation algorithm

• Authors: Maher I. Rajab
• Venue: ICCOMP'05 Proceedings of the 9th WSEAS International Conference on Computers
• Year: 2005

Since the introduction of epiluminescence microscopy (ELM), image analysis tools have been extended to the field of dermatology, as an attempt to algorithmically reproduce clinical evaluation. Accurate image segmentation of skin lesions is one of the key steps for useful, early, and non-invasive diagnosis of cutaneous melanomas. In this paper, a modified segmentation algorithm has been used to extract the true border that reveals the global structure irregularity (indentations and protrusions), which may suggest excessive cell growth or regression of a melanoma. The algorithm is applied to the blue channel of the RGB colour vectors to distinguish lesions from the skin and uses background noise reduction to enhance and filter the image of lesion. The algorithm also does not depend on the use of rigid threshold values, because an optimal thresholding algorithm "isodata algorithm" that is used determines an optimal threshold iteratively. Preliminary experiments are performed on diversity of clinical skin images and high resolution ELM images to verify the capability of the segmentation algorithm in extracting and characterizing the true features of the processed skin lesions. We demonstrate that we can enhance and delineate pigmented networks in skin lesions visually, and make them accessible for further analysis and classification.