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Diffuse optical tomography using generalized music algorithm

机译:使用广义音乐算法的漫射光学层析成像

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Diffuse optical tomography (DOT) is an emerging imaging modality to reconstruct the optical parameters of a highly scattering medium. However, ill-posedness and nonlinearity of light scattering make the DOT problem very difficult. We showed that DOT problem can be formulated as a multiple measurement vector (MMV) problem, and compressive sensing approach like S-OMP can be used. However, for a limited number of illumination patterns, the conventional compressed sensing (CS) approach for DOT was not satisfactory. The main objective of this paper is to propose a new non-iterative and exact reconstruction algorithm for the diffuse optical tomography problem that outperforms the conventional compressive sensing approach, thanks to a recently invented generalized MUSIC algorithm. Simulation results confirm that the new algorithm outperforms the previous algorithms and reliably reconstructs optical inhomogeneities.
机译:漫射光学断层扫描(点)是重建高散射介质的光学参数的新兴成像模块。然而,光散射的不良和非线性使得点问题非常困难。我们展示了点问题可以配制为多个测量向量(MMV)问题,并且可以使用像S-OMP等压缩感测方法。然而,对于有限数量的照明模式,用于点的传统压缩感测(CS)方法不令人满意。本文的主要目的是提出了一种新的非迭代和精确的重建算法,其弥漫性光学断层扫描问题优于传统的压缩感测方法,得益于最近发明的广义音乐算法。仿真结果证实,新算法优于先前的算法并可可靠地重建光学不均匀性。

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