Zobrazeno 1 - 10
of 2 699
pro vyhledávání: '"Pierre, Marc"'
Autor:
Judge, Arnaud, Judge, Thierry, Duchateau, Nicolas, Sandler, Roman A., Sokol, Joseph Z., Bernard, Olivier, Jodoin, Pierre-Marc
Performance of deep learning segmentation models is significantly challenged in its transferability across different medical imaging domains, particularly when aiming to adapt these models to a target domain with insufficient annotated data for effec
Externí odkaz:
http://arxiv.org/abs/2406.17902
Reinforcement learning (RL)-based tractography is a competitive alternative to machine learning and classical tractography algorithms due to its high anatomical accuracy obtained without the need for any annotated data. However, the reward functions
Externí odkaz:
http://arxiv.org/abs/2403.17845
Autor:
Painchaud, Nathan, Stym-Popper, Jérémie, Courand, Pierre-Yves, Thome, Nicolas, Jodoin, Pierre-Marc, Duchateau, Nicolas, Bernard, Olivier
Deep learning enables automatic and robust extraction of cardiac function descriptors from echocardiographic sequences, such as ejection fraction or strain. These descriptors provide fine-grained information that physicians consider, in conjunction w
Externí odkaz:
http://arxiv.org/abs/2401.07796
Monte Carlo Tree Search can be used for automated theorem proving. Holophrasm is a neural theorem prover using MCTS combined with neural networks for the policy and the evaluation. In this paper we propose to improve the performance of the Holophrasm
Externí odkaz:
http://arxiv.org/abs/2309.12711
Merging multiple input descriptors and supervisors in a deep neural network for tractogram filtering
One of the main issues of the current tractography methods is their high false-positive rate. Tractogram filtering is an option to remove false-positive streamlines from tractography data in a post-processing step. In this paper, we train a deep neur
Externí odkaz:
http://arxiv.org/abs/2307.05786
Privacy protection in medical data is a legitimate obstacle for centralized machine learning applications. Here, we propose a client-server image segmentation system which allows for the analysis of multi-centric medical images while preserving patie
Externí odkaz:
http://arxiv.org/abs/2305.13756
Recently, deep reinforcement learning (RL) has been proposed to learn the tractography procedure and train agents to reconstruct the structure of the white matter without manually curated reference streamlines. While the performances reported were co
Externí odkaz:
http://arxiv.org/abs/2305.09041
Autor:
Ling, Hang Jung, Painchaud, Nathan, Courand, Pierre-Yves, Jodoin, Pierre-Marc, Garcia, Damien, Bernard, Olivier
Deep learning-based methods have spearheaded the automatic analysis of echocardiographic images, taking advantage of the publication of multiple open access datasets annotated by experts (CAMUS being one of the largest public databases). However, the
Externí odkaz:
http://arxiv.org/abs/2305.01997