Computer-aided diagnosis (CAD) of retinal pathologies is a current active area in medical
image analysis. Due to the increasing use of retinal optical coherence tomography (OCT) …

Automatic and accurate classification of retinal optical coherence tomography (OCT) images
is essential to assist ophthalmologist in the diagnosis and grading of macular diseases …

Speckle noise in optical coherence tomography (OCT) impairs both the visual quality and
the performance of automatic analysis. Edge preservation is an important issue for speckle …

Optical coherence tomography (OCT) is an emerging imaging modality that has been widely
used in the field of biomedical imaging. In the recent past, it has found uses as a diagnostic …

Optical coherence tomography (OCT) is an efficient noninvasive bioimaging technique that
can measure retinal tissue. Considering the changes in the acquisition environment during …

As a major concern, the existence of unwanted energy and missing traces in seismic data
acquisition can degrade interpretation of such data after processing. Instead of analytical …

To assist ophthalmologists in diagnosing retinal abnormalities, Computer Aided Diagnosis
has played a significant role. In this paper, a particular Convolutional Neural Network based …

Raw optical coherence tomography (OCT) images typically are of low quality because
speckle noise blurs retinal structures, severely compromising visual quality and degrading …

Speckle noise is the main cause of poor optical coherence tomography (OCT) image quality.
Convolutional neural networks (CNNs) have shown remarkable performances for speckle …

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 …