A computer assisted diagnosis system for malignant melanoma using 3D skin surface texture features and artificial neural network

Ding, Y., Smith, L., Smith, M., Sun, J. and Warr, R. (2010) A computer assisted diagnosis system for malignant melanoma using 3D skin surface texture features and artificial neural network. International Journal of Modelling, Identification and Control, 9 (4). pp. 370-381. ISSN 1746-6172 Available from: http://eprints.uwe.ac.uk/17795

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Publisher's URL: http://www.inderscience.com/offer.php?id=33212

Abstract/Description

Abstract: It has been observed that disruptions in skin patterns are larger for malignant melanoma than for benign lesions. In contrast to existing work on 2D skin line patterns, this work proposes a computer assisted diagnosis system for malignant melanoma based on acquiring, analysing and classifying 3D skin surface texture features. Specifically, the 3D skin surface texture, in the form of surface normal vectors are acquired from a six-light photometric stereo device, the 3D features from the surface normals are extracted as the residuals between the acquired data and those from a 2D Gaussian model, while a three-layer feedforward neural classifier is used to classify the residuals. Preliminary studies on a sample set including 12 malignant melanomas and 34 benign lesions have given 91.7% sensitivity and 76.4% specificity using the proposed 3D skin surface normal features, which are better than 91.7% sensitivity and 25.7% specificity using the existing 2D skin line pattern features over the same lesion samples. This demonstrates that the proposed computer assisted diagnosis system of malignant melanoma based on 3D features offers an improvement over that based on 2D skin line patterns.

Item Type:Article
Uncontrolled Keywords:3D skin texture, a reference skin model, 2D Gaussian function, skin tilt pattern, skin cancer, slant pattern, multilayer perceptron, feature enhancement, artificial neural network, ANN, malignant melanoma
Faculty/Department:Faculty of Environment and Technology > Department of Engineering Design and Mathematics
ID Code:17795
Deposited By: Professor L. Smith
Deposited On:10 Dec 2012 16:26
Last Modified:18 May 2016 01:09

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