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Wavelet-based feature extraction applied to small-angle x-ray scattering patterns from breast tissue: a tool for differentiating between tissue types

G Falzon et al 2006 Phys. Med. Biol. 51 2465-2477   doi: 10.1088/0031-9155/51/10/007  Help

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G Falzon1,2, S Pearson1, R Murison2, C Hall3, K Siu4,5, A Evans6, K Rogers7 and R Lewis4,8
1 Department of Physics and Electronics, School of Biological, Biomedical and Molecular Sciences, University of New England, Armidale, NSW 2351, Australia
2 School of Mathematics, Statistics and Computer Science, University of New England, Armidale, NSW 2351, Australia
3 Daresbury Laboratory, Warrington, Cheshire WA4 4AD, UK
4 School of Physics, Monash University, Victoria 3800, Australia
5 Department of Medical Imaging and Radiation Sciences, Monash University, Victoria 3800, Australia
6 City Hospital Nottingham, Nottingham NG5 1PB, UK
7 Department of Materials and Medical Sciences, Cranfield University, Swindon SN6 8LA, UK
8 Monash Centre for Synchrotron Science, Monash University, Victoria 3800, Australia
E-mail: gfalzon@pobox.une.edu.au

Abstract. This paper reports on the application of wavelet decomposition to small-angle x-ray scattering (SAXS) patterns from human breast tissue produced by a synchrotron source. The pixel intensities of SAXS patterns of normal, benign and malignant tissue types were transformed into wavelet coefficients. Statistical analysis found significant differences between the wavelet coefficients describing the patterns produced by different tissue types. These differences were then correlated with position in the image and have been linked to the supra-molecular structural changes that occur in breast tissue in the presence of disease. Specifically, results indicate that there are significant differences between healthy and diseased tissues in the wavelet coefficients that describe the peaks produced by the axial d-spacing of collagen. These differences suggest that a useful classification tool could be based upon the spectral information within the axial peaks.

Print publication: Issue 10 (21 May 2006)
Received 20 December 2005, in final form 20 February 2006
Published 27 April 2006

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