29 October 2014 Automatic segmentation of psoriasis lesions
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Abstract
The automatic segmentation of psoriatic lesions is widely researched these years. It is an important step in Computer-aid methods of calculating PASI for estimation of lesions. Currently those algorithms can only handle single erythema or only deal with scaling segmentation. In practice, scaling and erythema are often mixed together. In order to get the segmentation of lesions area,this paper proposes an algorithm based on Random forests with color and texture features. The algorithm has three steps. The first step, the polarized light is applied based on the skin’s Tyndall-effect in the imaging to eliminate the reflection and Lab color space are used for fitting the human perception. The second step, sliding window and its sub windows are used to get textural feature and color feature. In this step, a feature of image roughness has been defined, so that scaling can be easily separated from normal skin. In the end, Random forests will be used to ensure the generalization ability of the algorithm. This algorithm can give reliable segmentation results even the image has different lighting conditions, skin types. In the data set offered by Union Hospital, more than 90% images can be segmented accurately.
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Yang Ning, Chenbo Shi, Li Wang, Chang Shu, "Automatic segmentation of psoriasis lesions", Proc. SPIE 9273, Optoelectronic Imaging and Multimedia Technology III, 927324 (29 October 2014); doi: 10.1117/12.2074372; https://doi.org/10.1117/12.2074372
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