8 citations · 15 across the 7 of their papers we have counts for
9 papers
Pulmonary Embolism Risk Stratification from CTPA and Medical Records: Vascular Graphs Are Not All You Need
Nathan Painchaud, Tristan Habémont, Morgane des Ligneris +6
Risk stratification for pulmonary embolism (PE) is critical for clinical decision-making. Stratification guidelines are based on patient medical records, parameters measured from c…
A Patient-Specific Pulmonary Arterial Tree Digital Twin to Extract Pulmonary Embolism Biomarkers
Morgane des Ligneris, Nathan Painchaud, Allan Serva +4
Pulmonary embolism, the obstruction of a pulmonary artery by a blood clot, is one of the leading causes of acute cardiovascular syndrome. In clinical practice, therapeutic decision…
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…
Shadow-Catcher: Looking Into Shadows to Detect Ghost Objects in Autonomous Vehicle 3D Sensing
Zhongyuan Hau, Soteris Demetriou, Luis Muñoz-González +1
LiDAR-driven 3D sensing allows new generations of vehicles to achieve advanced levels of situation awareness. However, recent works have demonstrated that physical adversaries can…
Strategies for Training Stain Invariant CNNs
Thomas Lampert, Odyssée Merveille, Jessica Schmitz +3
An important part of Digital Pathology is the analysis of multiple digitised whole slide images from differently stained tissue sections. It is common practice to mount consecutive…