Quantifications of asymmetries on the spectral bands of malignant melanoma using six sigma threshold as preprocessor - Sankaran, S; Sethumadhavan, G (Proceedings of third International Conference on Computational Intelligence and Information Technology, 2013)
Identifying and diagnosing skin cancer using non-invasive techniques have gained momentum in recent years. Such analysis requires trained medical professionals and hence it has become more of subjective. This paper presents a method to quantify the asymmetries of skin lesion. It is achieved by identifying the variations of the RGB spectrum of skin lesion images using Six Sigma threshold as the preprocessor. These identifications are achieved based on the underlying principles of Shewhart's Control Charts, which focus on the fact that the variability does exist in all repetitive processes. The heterogeneous color variation within the skin is considered as an assignable cause and is due to the secretion of excess melanin. These variations possess greater magnitude as compared to the chance causes due to the color variations found in normal skins. Based on these color variations, image is segmented into different homogeneous regions and the borders of the diseased regions are identified. A novel method to quantify the symmetries of the ROI after extracting the border of the lesion is proposed. It is achieved by counting the number of border pixels falls either sides of all the possible axes passing through the center of mass of ROI and by calculating an Asymmetric Index (AI). Results show that the method produces robust border detection and also ascertains the existence of asymmetries in the images of different degree of malignancy.