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