The resolution in optical coherence tomography imaging is an important parameter which
determines the size of the smallest features that can be visualized. Sparse sampling …

We present a nonlocal weighted sparse representation (NWSR) method for reconstruction of
retinal optical coherence tomography (OCT) images. To reconstruct a high signal-to-noise …

We demonstrate the usefulness of utilizing a segmentation step for improving the
performance of sparsity based image reconstruction algorithms. In specific, we will focus on …

Acquiring three dimensional image volumes with techniques such as Optical Coherence
Tomography (OCT) relies on reconstructing the tissue layers based on reflection of light from …

In this paper, we present a novel technique, based on compressive sensing principles, for
reconstruction and enhancement of multi-dimensional image data. Our method is a major …

Recently, compressive sampling has received significant attention as an emerging
technique for rapid volumetric imaging. We have previously investigated volumetric optical …

We applied compressed sensing (CS) to spectral domain optical coherence tomography
(SD-OCT). Namely, CS was applied to the spectral data in reconstructing A-mode images …

Optical coherence tomography (OCT) images are commonly affected by sidelobe artifacts
due to spectral non-uniformity and spectral leakage. Conventional frequency domain …

Optical coherence tomography (OCT) enables high-resolution and non-invasive 3D imaging
of the human retina but is inherently impaired by speckle noise. This paper introduces a …

We applied compressed sensing (CS) to spectral domain optical coherence tomography
(SD OCT) and studied its effectiveness. We tested the CS reconstruction by randomly …