title: Volumetric (3D) compressive sensing spectral domain optical coherence tomography.
abstract: In this work, we proposed a novel three-dimensional compressive sensing (CS) approach for spectral domain optical coherence tomography (SD OCT) volumetric image acquisition and reconstruction. Instead of taking a spectral volume whose size is the same as that of the volumetric image, our method uses a sub set of the original spectral volume that is under-sampled in all three dimensions, which reduces the amount of spectral measurements to less than 20% of that required by the Shan-non/Nyquist theory. The 3D image is recovered from the under-sampled spectral data dimension-by-dimension using the proposed three-step CS reconstruction strategy. Experimental results show that our method can significantly reduce the sampling rate required for a volumetric SD OCT image while preserving the image quality.
authors.affiliation: Department of Electrical and Computer Engineering, Johns Hopkins University 3400 N. Charles St, Baltimore, Maryland 21218, USA.
authors.forename: Daguang
authors.initials: D
authors.lastname: Xu
authors.affiliation: Department of Electrical and Computer Engineering, Johns Hopkins University 3400 N. Charles St, Baltimore, Maryland 21218, USA.
authors.forename: Yong
authors.initials: Y
authors.lastname: Huang
authors.affiliation: Department of Electrical and Computer Engineering, Johns Hopkins University 3400 N. Charles St, Baltimore, Maryland 21218, USA.
authors.forename: Jin U
authors.initials: JU
authors.lastname: Kang
keywords: (100.3010) Image reconstruction techniques; (170.4500) Optical coherence tomography