We present a novel fully automated algorithm for the detection of retinal diseases via optical
coherence tomography (OCT) imaging. Our algorithm utilizes multiscale histograms of …

We present a fully automatic algorithm to identify fluid-filled regions and seven retinal layers
on spectral domain optical coherence tomography images of eyes with diabetic macular …

Electroencephalogram (EEG) signals, generated during the neuron firing, are an effective
way of predicting such seizure and it is used widely in recent days for classifying and …

Automated segmentation of object boundaries or surfaces is crucial for quantitative image
analysis in numerous biomedical applications. For example, retinal surfaces in optical …

Accurate quantification of retinal layer thicknesses in mice as seen on optical coherence
tomography (OCT) is crucial for the study of numerous ocular and neurological diseases …

We propose a framework for automated detection of dry age-related macular degeneration
(AMD) and diabetic macular edema (DME) from retina optical coherence tomography (OCT) …

Microcystic macular edema (MME) manifests as small, hyporeflective cystic areas within the
retina. For reasons that are still largely unknown, a small proportion of patients with multiple …

Ophthalmic procedures demand precise surgical instrument control in depth, yet standard
operating microscopes supply limited depth perception. Current commercial microscope …

Accurate quantification of retinal structures in 3-D optical coherence tomography data of
eyes with pathologies provides clinically relevant information. We present an approach to …

Optical coherence tomography (OCT) yields high-resolution, three-dimensional images of
the retina. Reliable segmentation of the retinal layers is necessary for the extraction of …