Thomas M. Szalapski

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In previous research, a watershed-based algorithm was shown to be useful for automatic lesion segmentation in dermoscopy images, and was tested on a set of 100 benign and malignant melanoma images with the average of three sets of dermatologist-drawn borders used as the ground truth, resulting in an overall error of 15.98%. In this study, to reduce the(More)
BACKGROUND/PURPOSE Automatic lesion segmentation is an important part of computer-based image analysis of pigmented skin lesions. In this research, a watershed algorithm is developed and investigated for adequacy of skin lesion segmentation in dermoscopy images. METHODS Hair, black border and vignette removal methods are introduced as preprocessing steps.(More)
In this paper, an unsupervised approach based on Evolving Vector Quantization (EVQ) is presented for enhancing dermatology images for skin lesion segmentation. Vector Quantization (VQ) as a famous compression technique has been widely used in image signal compression and speech signal compression. The EVQ algorithm extends the Linde, Buzo, and Gray (LBG)(More)
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