Dermoscopic image segmentation based on modified GrabCut with octree color quantization

Vladimir Frants; Sos Agaian

doi:10.1117/12.2556699

23 April 2020 Dermoscopic image segmentation based on modified GrabCut with octree color quantization

Vladimir Frants, Sos Agaian

Proceedings Volume 11399, Mobile Multimedia/Image Processing, Security, and Applications 2020; 113990K (2020) https://doi.org/10.1117/12.2556699
Event: SPIE Defense + Commercial Sensing, 2020, Online Only

Abstract

Skin lesion segmentation (SLS) has a vital role in the early and precise diagnosis of skin cancer by computer-aided diagnosis (CAD) systems. But, the automatic SLS in dermoscopic images is a challenging task due to the substantial differences in color, texture, artifacts (hairs, gel bubbles, ruler markers), indistinct boundaries, low contrast, and varying sizes, position, and shapes of the lesion images. In the paper, we propose an extended GrabCut image segmentation algorithm for Foreground/Backgrounds dermoscopic image segmentation applications. The method integrates octree color quantization and a modified GrabCut method with a new energy function. Extensive computer simulation on ISIC 2017 has shown to compare favorably on both qualitative and quantitative evaluations with commonly used segmentation tools.

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Citation Download Citation

Vladimir Frants and Sos Agaian "Dermoscopic image segmentation based on modified GrabCut with octree color quantization", Proc. SPIE 11399, Mobile Multimedia/Image Processing, Security, and Applications 2020, 113990K (23 April 2020); https://doi.org/10.1117/12.2556699

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