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A new method describing border irregularity of pigmented lesions

Zhou, Yu; Smith, Melvyn; Smith, Lyndon; Warr, Robert

Authors

Yu Zhou

Profile Image

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

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

Robert Warr



Abstract

Background/purpose: Automatic quantitative characterization of border irregularity generating useful descriptors is a highly important task for computer-aided diagnosis of melanoma. This paper proposes a novel approach to describe the border irregularity of melanomas aiming at achieving higher recognition rates. Methods: By introducing a boundary characteristic description, which we call a centroid distance diagram (CDD), a compact-supported mapping, called the centroid distance curve, can be extracted from this diagram. The centroid distance curve establishes the projection from angular orientations to the sum of the lengths of those line segments connecting the lesion centroid and border points. Border irregularity descriptors generated from CDDs include the non-centroid-convexity index, the maximum-minimum distance indicator, the standard deviation of centroid distance curves and the maximum magnitude of non-zero frequency elements of centroid distance curves after discrete Fourier transforms. Upper limits of the error boundaries involved in these descriptors are estimated. Results: Experimental studies are based on 60 melanoma and 107 benign lesion images collected from local pigmented lesion clinics. By applying the proposed descriptors, receiver operating characteristic (ROC) curves are constructed by projecting the features into a linear space learned from samples. The optimal sensitivity and specificity for the proposed method are 74.2% and 72.6%. The total area enclosed by the corresponding ROC curve is 0.788. In addition, as the training and testing study for melanoma recognition in the literature is largely missing, a comprehensive comparative study is conducted by randomly dividing the data into two groups: one for training and one for testing. For the testing group, the best mean sensitivity obtained with the descriptors proposed in this paper reaches 71.8% and the standard deviation is 10.1%. The specificity for the testing group corresponding to the optimal sensitivity is 69.8%, with a standard deviation of 7.2%. Conclusion: This study suggests that in terms of sensitivity, descriptors extracted from CDDs are the most powerful ones in characterizing the border irregularity of melanomas. © 2010 John Wiley & Sons A/S.

Citation

Zhou, Y., Smith, M., Smith, L., & Warr, R. (2010). A new method describing border irregularity of pigmented lesions. Skin Research and Technology, 16(1), 66-76. https://doi.org/10.1111/j.1600-0846.2009.00403.x

Journal Article Type Article
Publication Date Feb 1, 2010
Journal Skin Research and Technology
Print ISSN 0909-752X
Electronic ISSN 1600-0846
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 16
Issue 1
Pages 66-76
DOI https://doi.org/10.1111/j.1600-0846.2009.00403.x
Keywords computer-aided diagnosis, border irregularity, discrete Fourier transform, melanoma, skin cancer, convexity
Public URL https://uwe-repository.worktribe.com/output/993685
Publisher URL http://dx.doi.org/10.1111/j.1600-0846.2009.00403.x