Abstract
Analysis of spatial frequency of Mueller matrix (MM) images in the Fourier domain yields quantifying parameters of anisotropy in the stromal region in normal and precancerous tissue sections of human uterine cervix. The spatial frequencies of MM elements reveal reliable information of microscopic structural organization arising from the different orientations of collagen fibers in the connective tissue and their randomization with disease progression. Specifically, the local disorder generated in the normal periodic and regular structure of collagen during the growth of the cervical cancer finds characteristic manifestation in the Fourier spectrum of the selected Mueller matrix elements encoding the anisotropy effects through retardance and birefringence. In contrast, Fourier spectra of differential polarization gated images are limited to only one orientation of collagen. Fourier spectra of first row elements M11, M12, M13, and M14 and first column elements M11, M21, M31, and M41 discriminates cervical inter-epithelial neoplasia (CIN)-I from normal cervical tissue samples with 95%-100% sensitivity and specificity. FFT spectra of first and fourth row elements classify CIN-I and CIN-II grades of cervical cancerous tissues with 90%-100% sensitivity and 87%-100% specificity. Normal and CIN-II grade samples are successfully discriminated through Fourier spectra of every MM element while that of M31 element arises as the key classifier among normal, CIN-I, and CIN-II grades of cervical cancer with 100% sensitivity and specificity. These results demonstrate the promise of spatial frequency analysis of Mueller matrix images as a novel, to the best of our knowledge, approach for cancer/precancer detection.
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