Open AccessHomotopic, non-local sparse reconstruction of optical coherence tomography imagery
Author(s) -
Chenyi Liu,
Alexander Wong,
Kostadinka Bizheva,
Paul Fieguth,
Hongxia Bie
Publication year - 2012
Publication title -
optics express
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.20.010200
Subject(s) - optical coherence tomography , computer science , computer vision , pixel , iterative reconstruction , artificial intelligence , image resolution , optics , ghost imaging , coherence (philosophical gambling strategy) , fidelity , mathematics , physics , statistics , telecommunications
The resolution in optical coherence tomography imaging is an important parameter which determines the size of the smallest features that can be visualized. Sparse sampling approaches have shown considerable promise in producing high resolution OCT images with fewer camera pixels, reducing both the cost and the complexity of an imaging system. In this paper, we propose a non-local approach to the reconstruction of high resolution OCT images from sparsely sampled measurements. An iterative strategy is introduced for minimizing a homotopic, non-local regularized functional in the spatial domain, subject to data fidelity constraints in the k-space domain. The novel algorithm was tested on human retinal, corneal, and limbus images, acquired in-vivo, demonstrating the effectiveness of the proposed approach in generating high resolution reconstructions from a limited number of camera pixels.