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Proceedings Paper

Image reconstruction from nonuniformly spaced samples in Fourier domain optical coherence tomography
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Paper Abstract

In this work, we use inverse imaging for object reconstruction from nonuniformly-spaced samples in Fourier domain optical coherence tomography (FD-OCT). We first model the FD-OCT system with a linear system of equations, where the source power spectrum and the nonuniformly-spaced sample positions are represented accurately. Then, we reconstruct the object signal directly from the nonuniformly-spaced wavelength measurements. With the inverse imaging method, we directly estimate the 2D cross-sectional object image instead of a set of independent A-line signals. By using the Total Variation (TV) as a constraint in the optimization process, we reduce the noise in the 2D object estimation. Besides TV, object sparsity is also used as a regularization for the signal reconstruction in FD-OCT. Experimental results demonstrate the advantages of our method, as we compare it with other methods.

Paper Details

Date Published: 10 February 2012
PDF: 8 pages
Proc. SPIE 8296, Computational Imaging X, 829610 (10 February 2012); doi: 10.1117/12.907331
Show Author Affiliations
Jun Ke, The Univ. of Hong Kong (Hong Kong, China)
Rui Zhu, The Univ. of Hong Kong (Hong Kong, China)
Edmund Y. Lam, The Univ. of Hong Kong (Hong Kong, China)


Published in SPIE Proceedings Vol. 8296:
Computational Imaging X
Charles A. Bouman; Ilya Pollak; Patrick J. Wolfe, Editor(s)

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