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Proceedings Paper

Assessment of robust reconstruction algorithms for compressive sensing spectral-domain optical coherence tomography
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Paper Abstract

In this paper, we performed an in-depth assessment of current state-of-the-art compressive sensing (CS) reconstruction algorithms, including YALL1, CSALSA, NESTA, SPGL1, TwIST and SpaRSA for use in spectral domain optical coherence tomography (SD-OCT). A brief description of mentioned algorithms and criterion in assessing performance between constraint and unconstraint algorithms are presented. The performance of all algorithms is initially assessed using a set of artificial noiseless A-scan signals with different spatial-domain dynamic range. Reconstruction error, computation time, noise tolerance and reliability of each algorithm are used as key metrics. A fair speed comparison is then implemented. Finally, computation time, SNR and local contrast of the algorithms are evaluated on real OCT Bscan data. Our results show that SPGL1 and YALL1 have moderately better performance.

Paper Details

Date Published: 22 February 2013
PDF: 14 pages
Proc. SPIE 8589, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XX, 85890C (22 February 2013); doi: 10.1117/12.2002476
Show Author Affiliations
Daguang Xu, Johns Hopkins Univ. (United States)
Yong Huang, Johns Hopkins Univ. (United States)
Jin U. Kang, Johns Hopkins Univ. (United States)

Published in SPIE Proceedings Vol. 8589:
Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XX
Carol J. Cogswell; Thomas G. Brown; Jose-Angel Conchello; Tony Wilson, Editor(s)

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