Enhanced 3D curvature pattern and melanoma diagnosis

Zhou, Y., Smith, M., Smith, L. and Farooq, A. (2010) Enhanced 3D curvature pattern and melanoma diagnosis. Computerized Medical Imaging and Graphics, 35. pp. 155-165. ISSN 0895-6111 Available from: http://eprints.uwe.ac.uk/17807

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Publisher's URL: http://dx.doi.org/10.1016/j.compmedimag.2010.10.00...


This article describes an enhanced curvature pattern basedmelanomadiagnosis system using convolution techniques and ensemble classifiers. We extract the 3D data of melanoma with a photometric stereo device first. Then differential forms of the melanoma surface can be extracted with the convolution method proposed. After extracting 3D based differential forms, statistical moments of enhanced principal curvatures of skin surfaces are calculated to describe the geometrical texture patterns. Finally, ensemble classifiers are constructed whose optimal mean sensitivity and specificity can reach 89.24 percent and 87.62 percent respectively. Comparisons with skin tilt/slant pattern based 3D shape characterization method and 2D methods like color variation and border irregularity are also included.

Item Type:Article
Uncontrolled Keywords:Shape analysis, melanoma, convolution, curvature, ensemble classifier
Faculty/Department:Faculty of Environment and Technology
ID Code:17807
Deposited By: Dr A. Farooq
Deposited On:27 Nov 2012 10:26
Last Modified:22 Apr 2016 23:18

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