This paper proposes a fully automatic method to segment the inner boundary of the bony
orbit in two different image modalities: magnetic resonance imaging (MRI) and computed …

Optical coherence tomography (OCT) has revolutionized ophthalmic clinical practice and
research, as a result of the high-resolution images that the method is able to capture in a …

Training deep learning methods for optical coherence tomography (OCT) retinal and
choroidal layer segmentation is a challenge when data is scarce. In medical image analysis …

Anterior segment optical coherence tomography (AS-OCT) is a fundamental ophthalmic
imaging technique. AS-OCT images can be examined by experts and segmented to provide …

Many clinical and research tasks rely critically upon the segmentation of tissue layers in
optical coherence tomography (OCT) images of the posterior eye (the retina and choroid) …

This study aimed to assess the utility of optic nerve head (onh) en-face images, captured
with scanning laser ophthalmoscopy (slo) during standard optical coherence tomography …

Quantification of the eye's anterior segment morphology from optical coherence tomography
(OCT) images is crucial for research and clinical decision-making, including the diagnosis …

For optimum performance, deep learning methods, such as those applied for retinal and
choroidal layer segmentation in optical coherence tomography (OCT) images, require …

Deep learning methods have demonstrated state-of-the-art performance for the
segmentation of the retina and choroid in optical coherence tomography (OCT) images …

In recent years, deep learning-based OCT segmentation methods have addressed many of
the limitations of traditional segmentation approaches and are capable of performing rapid …