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

Ding, Yi; Smith, Lyndon; Smith, Melvyn; Sun, Jiuai; Warr, Robert

Authors

Yi Ding

Lyndon Smith Lyndon.Smith@uwe.ac.uk
Professor in Computer Simulation and Machine

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Melvyn Smith Melvyn.Smith@uwe.ac.uk
Research Centre Director Vision Lab/Prof

Jiuai Sun

Robert Warr



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. Copyright © 2010 Inderscience Enterprises Ltd.

Citation

Ding, Y., Smith, L., Smith, M., Sun, J., & 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), 370-381. https://doi.org/10.1504/IJMIC.2010.033212

Journal Article Type Article
Publication Date May 1, 2010
Deposit Date Dec 10, 2012
Journal International Journal of Modelling, Identification and Control
Print ISSN 1746-6172
Electronic ISSN 1746-6180
Publisher Inderscience
Peer Reviewed Peer Reviewed
Volume 9
Issue 4
Pages 370-381
DOI https://doi.org/10.1504/IJMIC.2010.033212
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
Public URL https://uwe-repository.worktribe.com/output/984501
Publisher URL http://www.inderscience.com/offer.php?id=33212