2014 IEEE International Conference on Image Processing (ICIP) 2014
DOI: 10.1109/icip.2014.7025180
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Graph-based skin lesion segmentation of multispectral dermoscopic images

Abstract: Accurate skin lesion segmentation is critical for automated early skin cancer detection and diagnosis. We present a novel method to detect skin lesion borders in multispectral dermoscopy images. First, hairs are detected on infrared images and removed by inpainting visible spectrum images. Second, skin lesion is pre-segmented using a clustering of a superpixel partition. Finally, the pre-segmentation is globally regularized at the superpixel level and locally regularized in a narrow band at the pixel level.

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Cited by 8 publications
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“…The Dermoscopy Skin Lesion Multispectral Image Database (Lézoray et al, 2014) has 30 multispectral dermoscopic images with resolution 800x600 and are composed of 6 spectral bands (3 in visible spectrum light and 3 in infrared light).…”
Section: Existing Freely Available Skin Cancer Datasetsmentioning
confidence: 99%
“…The Dermoscopy Skin Lesion Multispectral Image Database (Lézoray et al, 2014) has 30 multispectral dermoscopic images with resolution 800x600 and are composed of 6 spectral bands (3 in visible spectrum light and 3 in infrared light).…”
Section: Existing Freely Available Skin Cancer Datasetsmentioning
confidence: 99%