Abstract
Contour extraction of skin tumors accurately is an important task for further feature generation of their borders and sur-faces to early diagnose melanomas. An integrated approach, combining visual attention model and GVF-snake, is pro-posed in the paper to provide a general framework for locating tumor boundaries in case of noise and boundaries with large concavity. For any skin image, the visual attention model is implemented to locate the Region of Interests (ROIs) based on saliency maps. Then an algorithm called GVF-snake is utilized to iteratively drive an initial contour, deriving from the extracted ROIs, towards real boundary of skin tumors by minimizing an energy function. It is shown from ex-periments that the proposed approach exceeds in two aspects compared with other contour-deforming methods: 1) ini-tial contours generated from saliency maps are definitely located at neighboring regions of real boundaries of skin tu-mors to speed up converges of contour deformation and achieve higher accuracy; 2) the method is not sensitive to nois-es on skins and initial contours extracted.
Highlights
Melanoma is known as one of the most malignant skin tumors probably appearing on any parts of human bodies
It is shown from experiments that the proposed approach exceeds in two aspects compared with other contour-deforming methods: 1) initial contours generated from saliency maps are definitely located at neighboring regions of real boundaries of skin tumors to speed up converges of contour deformation and achieve higher accuracy; 2) the method is not sensitive to noises on skins and initial contours extracted
Model based contour extraction of skin tumor faces difficulties in initial contour setting as it may be located at weaker gradient fields and failed to reach real boundary of a tumor
Summary
Melanoma is known as one of the most malignant skin tumors probably appearing on any parts of human bodies. Visual attention model becomes a hot research field in video monitoring systems to identify interested objects from visual information of environments. It is a process of selecting information based on saliency in images (bottom-up) and on task-related prior knowledge (up-down). In this paper an integrated approach of visual attention model and GVF-snake are proposed to perform automatic boundary extraction of skin tumors. Initial contour from the extracted ROI is iteratively evolved using GVF-snake model to locate the actual boundaries of skin tumors based on the criteria of energy minimization
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