title: Homotopic, non-local sparse reconstruction of optical coherence tomography imagery.
abstract: 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.
authors.affiliation: Department of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China. liucheny@gmail.com
authors.forename: Chenyi
authors.initials: C
authors.lastname: Liu
authors.forename: Alexander
authors.initials: A
authors.lastname: Wong
authors.forename: Kostadinka
authors.initials: K
authors.lastname: Bizheva
authors.forename: Paul
authors.initials: P
authors.lastname: Fieguth
authors.forename: Hongxia
authors.initials: H
authors.lastname: Bie
mesh_terms: D000465:Algorithms; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D041623:Tomography, Optical Coherence / Q000379:methods*