Jong Chul Ye just sent me the following
Hi Igor,Hope you are doing well. I would like to bring your attention to our new paper on compressed sensing application to diffuse optical tomography (DOT).This paper is an extension of our previous work on Compressive DOT (http://dx.doi.org/10.1109/TMI.2011.2125983) for recovery of absorption parameter variations. However, the main breakthrough in our new paper is that we first demonstrate that the joint sparsity principle is so general that it can be even used for the simultaneous reconstruction of both absorption and scattering parameters without updating Green's function. Unlike the common belief that cross-talk artifacts between absorption and scattering images are un-avoidable for the case of CW modulation, our joint sparse recovery approach significantly reduces such cross-talk artifacts. Moreover, our joint sparse recovery approach is faster than the conventional linearized approach even though our approach is exact and does not use any Born approximation.While this paper is for DOT problems, the same algorithmic appraoch can be used for electromagnetic inverse scattering problems from soft and hard obstacles. Enjoy !-Jong==========================================================Jong Chul Ye, Ph.DProfessorDept. of Bio and Brain EngineeringKAIST373-1 Guseong-Dong, Yuseong-GuDaejon 305-701, KoreaHomepage: http://bisp.kaist.ac.kr==========================================================
Joint sparsity-driven non-iterative simultaneous reconstruction of absorption and scattering in diffuse optical tomography by Okkyun Lee and Jong Chul Ye
Some optical properties of a highly scattering medium, such as tissue, can be reconstructed non-invasively by diffuse optical tomography (DOT). Since the inverse problem of DOT is severely ill-posed and nonlinear, iterative methods that update Green’s function have been widely used to recover accurate optical parameters. However, recent research has shown that the joint sparse recovery principle can provide an important clue in achieving reconstructions without an iterative update of Green’s function. One of the main limitations of the previous work is that it can only be applied to absorption parameter reconstruction. In this paper, we extended this theory to estimate the absorption and scattering parameters simultaneously when the background optical properties are known. The main idea for such an extension is that a joint sparse recovery step gives us unknown fluence on the estimated support set, which eliminates the nonlinearity in an integral equation for the simultaneous estimation of the optical parameters. Our numerical results show that the proposed algorithm reduces the cross-talk artifacts between the parameters and provides improved reconstruction results compared to existing methods.
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