A Novel Approach to Segment Skin Lesions in Dermoscopic Images Based on a Deformable Model

Abstract— Dermoscopy is an imaging technique that has been widely used in the diagnosis of skin lesions. However, its accuracy largely depends on the dermatologist’s experience; thus, computer-aided diagnosis techniques are required. In this paper, a novel approach based on a deformable model is proposed to handle the segmentation of skin lesions in dermoscopic images. The RGB color space is converted so that the color information contained in the images can be used effectively to differentiate normal skin and skin lesions; and the differences in the color channels are combined to-gether to define the speed function and the stopping criterion of the deformable model. This novel approach is robust against the noise, and provides an effective and flexible segmentation. Two image databases were used to test the performance of the novel approach and the segmentation results obtained were satisfactory. Quantitative analysis on 250 dermoscopic images showed that the novel algorithm outperformed other state-of-the-art algorithms. Also, using comparative data, the reliability and the implementation issues. Dermoscopy is a noninvasive imaging technique that has been developed to assist skin cancer diagnoses. A microscope with incident light and oil immersion is used to visualize the subsurface structures of the skin. This technique enables more details of colors and textures of the skin lesions to be observed. < final year projects >