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Proceedings Paper

Two-dimensional compressive sensing in spectral domain optical coherence tomography
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Paper Abstract

In this paper, we proposed a novel compressive sensing (CS) method in spectral domain optical coherence tomography (SD OCT), which reconstructs B-scan image using a subset of the spectral data that is under-sampled in both axial and lateral dimensions. Thus a fraction of the A-scans for a B-scan are acquired; the spectral data of each acquired A-scan is under-sampled. Compared with the previous studies, our method further reduces the overall size of the spectral measurements. Experimental results show that our approach can obtain high quality B-scan image using 25% spectral data, which takes 50% number of A-scans and acquires 50% spectral data for each selected A-scan.

Paper Details

Date Published: 9 March 2015
PDF: 6 pages
Proc. SPIE 9330, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXII, 93301A (9 March 2015); doi: 10.1117/12.2079398
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. 9330:
Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXII
Thomas G. Brown; Carol J. Cogswell; Tony Wilson, Editor(s)

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