Paper
9 March 2015 Two-dimensional compressive sensing in spectral domain optical coherence tomography
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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.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Daguang Xu, Yong Huang, and Jin U. Kang "Two-dimensional compressive sensing in spectral domain optical coherence tomography", Proc. SPIE 9330, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXII, 93301A (9 March 2015); https://doi.org/10.1117/12.2079398
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Cited by 1 scholarly publication.
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KEYWORDS
Optical coherence tomography

Data acquisition

Compressed sensing

Image quality

3D metrology

Wavelets

3D image processing

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