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Conf Proc IEEE Eng Med Biol Soc. 2012;2012:4002-5. doi: 10.1109/EMBC.2012.6346844.

An incremental approach to pigmented skin lesion segmentation with classification refinements in uncertain regions.

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Institute for Infocomm Research, A*STAR, Singapore 138632. wxiong@i2r,


Skin lesion segmentation in dermatoscopic images is difficult because there are large inter variations in shape, size, color, and texture between lesions and skin types. Hence, computational features learned from a training set of lesion images may not be applicable to other lesion images. In this paper, we propose an incremental method for lesion segmentation. It leverages the Expectation-Maximization algorithm to find an initial segmentation. A new adaptive method is proposed to define two types of segmented regions: the high-confident and the low-confident. We train a support vector machine, using computational features from the high-confident regions, to further refine segmentation and, hence, achieve improved results for the low-confident regions. Validation experiments of our proposed method are performed on 319 dermatoscopy images and we have achieved good results with precision and recall to be 0.864 and 0.875 respectively.

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