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Analysis of the contour structural irregularity of skin lesions using wavelet decomposition
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Ma, Li and Staunton, Richard C. (2013) Analysis of the contour structural irregularity of skin lesions using wavelet decomposition. Pattern Recognition, Vol.46 (No.1). pp. 98-106. doi:10.1016/j.patcog.2012.07.001 ISSN 00313203.
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WRAP_Staunton_PrePrint_PR_D_11_01189R2.pdf - Accepted Version Download (937Kb) | Preview |
Official URL: http://dx.doi.org/10.1016/j.patcog.2012.07.001
Abstract
The boundary irregularity of skin lesions is of clinical significance for the early detection of
malignant melanomas and to distinguish them from other lesions such as benign moles. The
structural components of the contour are of particular importance. To extract the structure from
the contour, wavelet decomposition was used as these components tend to locate in the lower
frequency sub-bands. Lesion contours were modeled as signatures with scale normalization to
give position and frequency resolution invariance. Energy distributions among different wavelet
sub-bands were then analyzed to extract those with significant levels and differences to enable
maximum discrimination.
Based on the coefficients in the significant sub-bands, structural components from the original
contours were modeled, and a set of statistical and geometric irregularity descriptors researched
that were applied at each of the significant sub-bands. The effectiveness of the descriptors was
measured using the Hausdorff distance between sets of data from melanoma and mole contours.
The best descriptor outputs were input to a back projection neural network to construct a
combined classifier system. Experimental results showed that thirteen features from four
sub-bands produced the best discrimination between sets of melanomas and moles, and that a
small training set of nine melanomas and nine moles was optimum.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QA Mathematics R Medicine > RC Internal medicine |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||
Library of Congress Subject Headings (LCSH): | Melanoma -- Diagnosis, Skin -- Diseases -- Diagnosis, Wavelets (Mathematics) | ||||
Journal or Publication Title: | Pattern Recognition | ||||
Publisher: | Elsevier BV | ||||
ISSN: | 00313203 | ||||
Official Date: | January 2013 | ||||
Dates: |
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Volume: | Vol.46 | ||||
Number: | No.1 | ||||
Page Range: | pp. 98-106 | ||||
DOI: | 10.1016/j.patcog.2012.07.001 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access | ||||
Date of first compliant deposit: | 22 December 2015 | ||||
Date of first compliant Open Access: | 22 December 2015 | ||||
Funder: | Guo jia zi ran ke xue ji jin wei yuan hui (China) [National Natural Science Foundation of China] (NSFC) | ||||
Grant number: | 60775016 (NSFC) |
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