Diffuse optical tomography using generalized music algorithm

Ok Kyun Lee, Jongmin Kim, Yoram Bresler, Jong Chul Ye

Abstract: 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.