Hair removal methods: A comparative study for dermoscopy images |
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Authors: | Qaisar Abbas ME Celebi Irene Fondón García |
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Institution: | aDepartment of Computer Science and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China;bCenter for Biomedical Imaging and Bioinformatics, Key Laboratory of Image Processing and Intelligent Control of Ministry of Education, Wuhan, China;cDepartment of Computer Science, Louisiana State University, Shreveport, LA, USA;dDepartment of Signal Theory and Communications, School of Engineering Path of Discovery, Sevilla, Spain |
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Abstract: | Removal and restoration of hair and hair-like regions within skin lesion images is needed so features within lesions can be more effectively analyzed for benign lesions, cancerous lesions, and for cancer discrimination. This paper refers to “melanoma texture” as a rationale for supporting the need for the proposed hair detection and repair techniques, which incompletely represents why hair removal is an important operation for skin lesion analysis. A comparative study of the state-of-the-art hair-repaired methods with a novel algorithm is also proposed by morphological and fast marching schemes. The hair-repaired techniques are evaluated in terms of computational, performance and tumor-disturb patterns (TDP) aspects. The comparisons have been done among (i) linear interpolation, inpainting by (ii) non-linear partial differential equation (PDE) and (iii) exemplar-based repairing techniques. The performance analysis of hair detection quality, was based on the evaluation of the hair detection error (HDE), quantified by statistical metrics and manually used to determine the hair lines from a dermatologist as the ground truth. The results are presented on a set of 100 dermoscopic images. For the two characteristics measured in the experiments the best method is the fast marching hair removal algorithm (HDE: 2.98%, TDP: 4.21%). This proposed algorithm repaired the texture of the melanoma, which becomes consistent with human vision. The comparisons results obtained, indicate that hair-repairing algorithm based on the fast marching method achieve an accurate result. |
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Keywords: | Skin cancer Dermoscopy Melanoma Hair segmentation Linear interpolation Image inpainting PDE Fast marching |
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