21 April 2016 Total variation based reconstruction of scattering inhomogeneities in tissue from time-resolved optical projections
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The important advantage of diffuse optical tomography (DOT) is the possibility of tissue functional diagnosis. However the possibility implements if only we separately reconstruct the spatial distributions of optical parameters, specifically the absorption and scattering coefficients. We have recently demonstrated that time-domain DOT based on the perturbation model by Lyubimov is capable of reconstructing absorbing inhomogeneities in tissue with a DOT high spatial resolution (better than 3 mm at a depth of 4 cm). This paper continues our research and focuses on the reconstruction of scattering inhomogeneities. We consider the flat layer transmission geometry which is traditional for optical mammography, and use diffusion approximation to derive analytical expressions for weight functions responsible for the reconstruction of scattering inhomogeneities. To confirm that our calculations are correct we perform a numerical experiment where we reconstruct a rectangular scattering object 10×8 cm in size with 4 circular scattering macroinhomogeneities 4 mm in diameter each, and a randomly inhomogeneous scattering structure. The inverse DOT problem is solved with a multiplicative algebraic reconstruction technique where interim iterations are processed through total variation norm minimization. The results suggest that our DOT method reliably resolves the scattering macroinhomogeneities of mentioned size against a randomly inhomogeneous structure.
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Alexander B. Konovalov, Alexander B. Konovalov, Vitaly V. Vlasov, Vitaly V. Vlasov, "Total variation based reconstruction of scattering inhomogeneities in tissue from time-resolved optical projections", Proc. SPIE 9917, Saratov Fall Meeting 2015: Third International Symposium on Optics and Biophotonics and Seventh Finnish-Russian Photonics and Laser Symposium (PALS), 99170S (21 April 2016); doi: 10.1117/12.2229846; https://doi.org/10.1117/12.2229846

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