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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 Falzon1,2, S Pearson1, R Murison2, C Hall3, K Siu4,5, A Evans6, K Rogers7 and R Lewis4,8

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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.


PACS

87.59.E- Mammography

87.57.N- Image analysis

02.30.Uu Integral transforms

87.14.E- Proteins

87.19.X- Diseases

87.15.B- Structure of biomolecules

Subjects

Mathematical physics

Biological physics

Medical physics

Dates

Issue 10 (21 May 2006)

Received 20 December 2005, in final form 20 February 2006

Published 27 April 2006



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