Easy-interactive and quick psoriasis lesion segmentation

Guoli Ma; Bei He; Wenming Yang; Chang Shu

doi:10.1117/12.2038065

19 December 2013 Easy-interactive and quick psoriasis lesion segmentation

Guoli Ma, Bei He, Wenming Yang, Chang Shu

Proceedings Volume 9045, 2013 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology; 90450T (2013) https://doi.org/10.1117/12.2038065
Event: International Conference on Optical Instruments and Technology (OIT2013), 2013, Beijing, China

Abstract

This paper proposes an interactive psoriasis lesion segmentation algorithm based on Gaussian Mixture Model (GMM). Psoriasis is an incurable skin disease and affects large population in the world. PASI (Psoriasis Area and Severity Index) is the gold standard utilized by dermatologists to monitor the severity of psoriasis. Computer aid methods of calculating PASI are more objective and accurate than human visual assessment. Psoriasis lesion segmentation is the basis of the whole calculating. This segmentation is different from the common foreground/background segmentation problems. Our algorithm is inspired by GrabCut and consists of three main stages. First, skin area is extracted from the background scene by transforming the RGB values into the YCbCr color space. Second, a rough segmentation of normal skin and psoriasis lesion is given. This is an initial segmentation given by thresholding a single gaussian model and the thresholds are adjustable, which enables user interaction. Third, two GMMs, one for the initial normal skin and one for psoriasis lesion, are built to refine the segmentation. Experimental results demonstrate the effectiveness of the proposed algorithm.

Citation Download Citation

Guoli Ma, Bei He, Wenming Yang, and Chang Shu "Easy-interactive and quick psoriasis lesion segmentation", Proc. SPIE 9045, 2013 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, 90450T (19 December 2013); https://doi.org/10.1117/12.2038065

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