Distinguishing autofluorescence of normal, benign, and cancerous breast tissues through wavelet domain correlation studies

摘要

Using the multiresolution ability of wavelets and effectiveness of singular value decomposition (SVD)nto identify statistically robust parameters, we find a number of local and global features, capturing spectralncorrelations in the co- and cross-polarized channels, at different scales (of human breast tissues). The copolarizedncomponent, being sensitive to intrinsic fluorescence, shows different behavior for normal, benign, and cancerousntissues, in the emission domain of known fluorophores, whereas the perpendicular component, being more pronento the diffusive effect of scattering, points out differences in the Kernel–Smoother density estimate employed tonthe principal components, between malignant, normal, and benign tissues. The eigenvectors, corresponding tonthe dominant eigenvalues of the correlation matrix in SVD, also exhibit significant differences between the threentissue types, which clearly reflects the differences in the spectral correlation behavior. Interestingly, the mostnsignificant distinguishing feature manifests in the perpendicular component, corresponding to porphyrin emissionnrange in the cancerous tissue. The fact that perpendicular component is strongly influenced by depolarization,nand porphyrin emissions in cancerous tissue has been found to be strongly depolarized, may be the possible causenof the above observation.