@inproceedings{464f38846fc04c1a93c9d0b00374cc97,
title = "Two-dimensional compressive sensing in spectral domain optical coherence tomography",
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.",
keywords = "Compressive sensing, image processing, optical coherence tomography, reconstruction algorithm",
author = "Daguang Xu and Yong Huang and Kang, \{Jin U.\}",
note = "Publisher Copyright: {\textcopyright} 2015 SPIE.; Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXII ; Conference date: 09-02-2015 Through 12-02-2015",
year = "2015",
doi = "10.1117/12.2079398",
language = "English",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Brown, \{Thomas G.\} and Cogswell, \{Carol J.\} and Tony Wilson",
booktitle = "Three-Dimensional and Multidimensional Microscopy",
address = "United States",
}