109 citations · 164 across the 6 of their papers we have counts for
7 papers
Lirot.ai: A Novel Platform for Crowd-Sourcing Retinal Image Segmentations
Jonathan Fhima, Jan Van Eijgen, Moti Freiman +2
Introduction: For supervised deep learning (DL) tasks, researchers need a large annotated dataset. In medical data science, one of the major limitations to develop DL models is the…
PVBM: A Python Vasculature Biomarker Toolbox Based On Retinal Blood Vessel Segmentation
Jonathan Fhima, Jan Van Eijgen, Ingeborg Stalmans +3
Introduction: Blood vessels can be non-invasively visualized from a digital fundus image (DFI). Several studies have shown an association between cardiovascular risk and vascular f…
FundusQ-Net: a Regression Quality Assessment Deep Learning Algorithm for Fundus Images Quality Grading
Or Abramovich, Hadas Pizem, Jan Van Eijgen +5
Objective: Ophthalmological pathologies such as glaucoma, diabetic retinopathy and age-related macular degeneration are major causes of blindness and vision impairment. There is a…
Automatic Segmentation of the Optic Nerve Head Region in Optical Coherence Tomography: A Methodological Review
Rita Marques, Danilo Andrade De Jesus, João Barbosa Breda +6
The optic nerve head represents the intraocular section of the optic nerve (ONH), which is prone to damage by intraocular pressure. The advent of optical coherence tomography (OCT)…
Pointwise visual field estimation from optical coherence tomography in glaucoma: a structure-function analysis using deep learning
Ruben Hemelings, Bart Elen, João Barbosa Breda +4
Background/Aims: Standard Automated Perimetry (SAP) is the gold standard to monitor visual field (VF) loss in glaucoma management, but is prone to intra-subject variability. We dev…
Deep learning on fundus images detects glaucoma beyond the optic disc
Ruben Hemelings, Bart Elen, João Barbosa-Breda +3
Although unprecedented sensitivity and specificity values are reported, recent glaucoma detection deep learning models lack in decision transparency. Here, we propose a methodology…
Pathological myopia classification with simultaneous lesion segmentation using deep learning
Ruben Hemelings, Bart Elen, Matthew B. Blaschko +3
This investigation reports on the results of convolutional neural networks developed for the recently introduced PathologicAL Myopia (PALM) dataset, which consists of 1200 fundus i…