Open Access3-D compressed sensing optical coherence tomography using predictive coding
Author(s) -
James McLean,
Christine P. Hendon
Publication year - 2021
Publication title -
biomedical optics express
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.362
H-Index - 86
ISSN - 2156-7085
DOI - 10.1364/boe.421848
Subject(s) - optical coherence tomography , computer science , computer vision , artificial intelligence , iterative reconstruction , noise reduction , compressed sensing , sampling (signal processing) , pattern recognition (psychology) , optics , filter (signal processing) , physics
We present a compressed sensing (CS) algorithm and sampling strategy for reconstructing 3-D Optical Coherence Tomography (OCT) image volumes from as little as 10% of the original data. Reconstruction using the proposed method, Denoising Predictive Coding (DN-PC), is demonstrated for five clinically relevant tissue types including human heart, retina, uterus, breast, and bovine ligament. DN-PC reconstructs the difference between adjacent b-scans in a volume and iteratively applies Gaussian filtering to improve image sparsity. An a-line sampling strategy was developed that can be easily implemented in existing Spectral-Domain OCT systems and reduce scan time by up to 90%.