Compressive SD-OCT: The application of compressed sensing in spectral domain optical coherence tomography

Xuan Liu, Jin U. Kang

Research output: Contribution to journalArticlepeer-review

69 Scopus citations

Abstract

We applied compressed sensing (CS) to spectral domain optical coherence tomography (SD OCT) and studied its effectiveness. We tested the CS reconstruction by randomly undersampling the k-space SD OCT signal. We achieved this by applying pseudo-random masks to sample 62.5%, 50%, and 37.5% of the CCD camera pixels. OCT images are reconstructed by solving an optimization problem that minimizes the l1 norm of a transformed image to enforce sparsity, subject to data consistency constraints. CS could allow an array detector with fewer pixels to reconstruct high resolution OCT images while reducing the total amount of data required to process the images.

Original languageEnglish (US)
Pages (from-to)22010-22019
Number of pages10
JournalOptics Express
Volume18
Issue number21
DOIs
StatePublished - Oct 11 2010
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics

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