12 February 2008 Multi-view optical tomography using L1 data fidelity and sparsity constraint
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This paper describes a novel reconstruction algorithm for microscopy axial tomography, which reconstructs a 3-D volume using multiple tilted views through an off-centered aperture and numerical processing. The main contribution of this paper is a derivation of novel optimization criterion and algorithm for a cost function with L1 fidelity term and sparsity constraint. A parallel coordinate descent (PCD) algorithm has been derived as an efficient optimization methods, which corresponds to iterative application of projection and nonlinear back-projection using median. Numerical simulation results using synthetic and real microscopy data show that accurate reconstruction can be obtained rapidly, and interference artifacts from high contrast objects in a volume can be removed efficiently. Our algorithm is quite general, and can be used for many other tomosynthesis applications with limited number of views.
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Jaeduck Jang, Jong Chul Ye, "Multi-view optical tomography using L1 data fidelity and sparsity constraint", Proc. SPIE 6861, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XV, 68610G (12 February 2008); doi: 10.1117/12.762412; https://doi.org/10.1117/12.762412

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