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

Jun Ke; Rui Zhu; Edmund Y. Lam

doi:10.1117/12.907331

10 February 2012 Image reconstruction from nonuniformly spaced samples in Fourier domain optical coherence tomography

Jun Ke, Rui Zhu, Edmund Y. Lam

Proceedings Volume 8296, Computational Imaging X; 829610 (2012) https://doi.org/10.1117/12.907331
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States

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.

Citation Download Citation

Jun Ke, Rui Zhu, and Edmund Y. Lam "Image reconstruction from nonuniformly spaced samples in Fourier domain optical coherence tomography", Proc. SPIE 8296, Computational Imaging X, 829610 (10 February 2012); https://doi.org/10.1117/12.907331

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