5 papers
Uncertainty guided semi-supervised segmentation of retinal layers in OCT images
Suman Sedai, Bhavna Antony, Ravneet Rai +5
Deep convolutional neural networks have shown outstanding performance in medical image segmentation tasks. The usual problem when training supervised deep learning methods is the l…
Self-supervised Denoising via Diffeomorphic Template Estimation: Application to Optical Coherence Tomography
Guillaume Gisbert, Neel Dey, Hiroshi Ishikawa +3
Optical Coherence Tomography (OCT) is pervasive in both the research and clinical practice of Ophthalmology. However, OCT images are strongly corrupted by noise, limiting their int…
Dueling Deep Q-Network for Unsupervised Inter-frame Eye Movement Correction in Optical Coherence Tomography Volumes
Yasmeen M. George, Suman Sedai, Bhavna J. Antony +4
In optical coherence tomography (OCT) volumes of retina, the sequential acquisition of the individual slices makes this modality prone to motion artifacts, misalignments between ad…
Inference of visual field test performance from OCT volumes using deep learning
Stefan Maetschke, Bhavna Antony, Hiroshi Ishikawa +3
Visual field tests (VFT) are pivotal for glaucoma diagnosis and conducted regularly to monitor disease progression. Here we address the question to what degree aggregate VFT measur…
A feature agnostic approach for glaucoma detection in OCT volumes
Stefan Maetschke, Bhavna Antony, Hiroshi Ishikawa +3
Optical coherence tomography (OCT) based measurements of retinal layer thickness, such as the retinal nerve fibre layer (RNFL) and the ganglion cell with inner plexiform layer (GCI…