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Proceedings Paper

Multi-view optical tomography using L1 data fidelity and sparsity constraint
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Paper Abstract

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.

Paper Details

Date Published: 12 February 2008
PDF: 8 pages
Proc. SPIE 6861, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XV, 68610G (12 February 2008); doi: 10.1117/12.762412
Show Author Affiliations
Jaeduck Jang, Korea Advanced Institute of Science and Technology (South Korea)
Jong Chul Ye, Korea Advanced Institute of Science and Technology (South Korea)


Published in SPIE Proceedings Vol. 6861:
Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XV
Jose-Angel Conchello; Carol J. Cogswell; Tony Wilson; Thomas G. Brown, Editor(s)

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