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

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. © 2012 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).