322 citations
- Centre National de la Recherche ScientifiqueFR85 papers
- IMT AtlantiqueFR70 papers
- Laboratoire de Mathématiques de Bretagne AtlantiqueFR67 papers
- Laboratoire des Sciences et Techniques de l’Information de la Communication et de la ConnaissanceFR63 papers
- Université de Bretagne SudFR58 papers
- InsermFR26 papers
- Laboratoire de Traitement de l'Information MédicaleFR21 papers
- Université Grenoble AlpesFR16 papers
- École nationale supérieure de techniques avancées BretagneFR15 papers
- Centre Hospitalier Régional Universitaire de BrestFR13 papers
- École nationale d'ingénieurs de BrestFR10 papers
- Shandong UniversityCN10 papers
15 papers · 1 filter
crossMoDA Challenge: Evolution of Cross-Modality Domain Adaptation Techniques for Vestibular Schwannoma and Cochlea Segmentation from 2021 to 2023
Navodini Wijethilake, Reuben Dorent, Marina Ivory +38
The cross-Modality Domain Adaptation (crossMoDA) challenge series, initiated in 2021 in conjunction with the International Conference on Medical Image Computing and Computer Assist…
Goal-Oriented Source Coding using LDPC Codes for Compressed-Domain Image Classification
Ahcen Aliouat, Elsa Dupraz
In the emerging field of goal-oriented communications, the focus has shifted from reconstructing data to directly performing specific learning tasks, such as classification, segmen…
Generalization performance of neural mapping schemes for the space-time interpolation of satellite-derived ocean colour datasets
Thi Thuy Nga Nguyen, Clément Dorffer, Frédéric Jourdin +1
Neural mapping schemes have become appealing approaches to deliver gap-free satellite-derived products for sea surface tracers. The generalization performance of these learning-bas…
Observation-only learning of neural mapping schemes for gappy satellite-derived ocean colour parameters
Clément Dorffer, Frédéric Jourdin, Thi Thuy Nga Nguyen +3
Monitoring optical properties of coastal and open ocean waters is crucial to assessing the health of marine ecosystems. Deep learning offers a promising approach to address these e…
Scale-specific auxiliary multi-task contrastive learning for deep liver vessel segmentation
Amine Sadikine, Bogdan Badic, Jean-Pierre Tasu +4
Extracting hepatic vessels from abdominal images is of high interest for clinicians since it allows to divide the liver into functionally-independent Couinaud segments. In this res…
Multibranch Generative Models for Multichannel Imaging with an Application to PET/CT Synergistic Reconstruction
Noel Jeffrey Pinton, Alexandre Bousse, Catherine Cheze-Le-Rest +1
This paper presents a novel approach for learned synergistic reconstruction of medical images using multibranch generative models. Leveraging variational autoencoders (VAEs), our m…