activity
20192021
most citedJoint segmentation and classification of retinal arteries/veins from fundus images

106 citations · 126 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV202117 cited

Adaptable Deformable Convolutions for Semantic Segmentation of Fisheye Images in Autonomous Driving Systems

Clément Playout, Ola Ahmad, Freddy Lecue +1

Advanced Driver-Assistance Systems rely heavily on perception tasks such as semantic segmentation where images are captured from large field of view (FoV) cameras. State-of-the-art…

eess.IV2020

Three-dimensional Segmentation of the Scoliotic Spine from MRI using Unsupervised Volume-based MR-CT Synthesis

Enamundram M. V. Naga Karthik, Catherine Laporte, Farida Cheriet

Vertebral bone segmentation from magnetic resonance (MR) images is a challenging task. Due to the inherent nature of the modality to emphasize soft tissues of the body, common thre…

cs.CV20203 cited

End-to-End Deep Learning Model for Cardiac Cycle Synchronization from Multi-View Angiographic Sequences

Raphaël Royer-Rivard, Fantin Girard, Nagib Dahdah +1

Dynamic reconstructions (3D+T) of coronary arteries could give important perfusion details to clinicians. Temporal matching of the different views, which may not be acquired simult…

q-bio.QM2019

Laplacian Flow Dynamics on Geometric Graphs for Anatomical Modeling of Cerebrovascular Networks

Rafat Damseh, Patrick Delafontaine-Martel, Philippe Pouliot +2

Generating computational anatomical models of cerebrovascular networks is vital for improving clinical practice and understanding brain oxygen transport. This is achieved by extrac…

cs.CV2019106 cited

Joint segmentation and classification of retinal arteries/veins from fundus images

Fantin Girard, Conrad Kavalec, Farida Cheriet

Objective Automatic artery/vein (A/V) segmentation from fundus images is required to track blood vessel changes occurring with many pathologies including retinopathy and cardiovasc…