Automated Pre-processing Method for Dermoscopic Images and its Application to Pigmented Skin Lesion Segmentation

摘要

In this paper, we put forward a new pre-processing scheme for automatic analysis of dermoscopic images. Our contributions are two-fold. First, we present a procedure, an extension of previous approaches, which succeeds in removing confounding factors from dermoscopic images: these include shading induced by imaging non-flat skin surfaces and the effect of light-intensity falloff toward the edges of the dermoscopic image. This procedure is shown to facilitate the detection and removal of artifacts such as hairs as well. Second, we present a novel simple yet effective greyscale conversion approach that is based on physics and biology of human skin. Our proposed greyscale image provides high separability between a pigmented lesion and normal skin surrounding it. Finally, using our pre-processing scheme, we perform segmentation based on simple grey-level thresholding, with results outperforming the state of the art.