8 citations · 15 across the 7 of their papers we have counts for
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The R-Vessel-X Project
Abir Affane, Mohamed Amine Chetoui, Jonas Lamy +16
1) Objectives: This technical report presents a synthetic summary and the principal outcomes of the project R-Vessel-X ("Robust vascular network extraction and understanding within…
A plug-and-play framework for curvilinear structure segmentation based on a learned reconnecting regularization
Sophie Carneiro-Esteves, Antoine Vacavant, Odyssée Merveille
Curvilinear structures are present in various fields in image processing such as blood vessels in medical imaging or roads in remote sensing. Their detection is crucial for many ap…
Guidelines for Cerebrovascular Segmentation: Managing Imperfect Annotations in the context of Semi-Supervised Learning
Pierre Rougé, Pierre-Henri Conze, Nicolas Passat +1
Segmentation in medical imaging is an essential and often preliminary task in the image processing chain, driving numerous efforts towards the design of robust segmentation algorit…
Restoring Connectivity in Vascular Segmentation using a Learned Post-Processing Model
Sophie Carneiro-Esteves, Antoine Vacavant, Odyssée Merveille
Accurate segmentation of vascular networks is essential for computer-aided tools designed to address cardiovascular diseases. Despite more than thirty years of research, it remains…
Cascaded multitask U-Net using topological loss for vessel segmentation and centerline extraction
Pierre Rougé, Nicolas Passat, Odyssée Merveille
Vessel segmentation and centerline extraction are two crucial preliminary tasks for many computer-aided diagnosis tools dealing with vascular diseases. Recently, deep-learning base…