88 citations · 191 across the 3 of their papers we have counts for
4 papers
A foundation for systematic analysis of transformers and RNNs for tractography
Emmanuelle Renauld, Philippe Poulin, Hugo Larochelle +2
Machine learning (ML) has emerged as a promising approach for improving diffusion MRI (dMRI) tractography, a task that remains limited by the intrinsic tension between local diffus…
FIESTA: Autoencoders for accurate fiber segmentation in tractography
Félix Dumais, Jon Haitz Legarreta, Carl Lemaire +7
White matter bundle segmentation is a cornerstone of modern tractography to study the brain's structural connectivity in domains such as neurological disorders, neurosurgery, and a…
Tractography and machine learning: Current state and open challenges
Philippe Poulin, Daniel Jörgens, Pierre-Marc Jodoin +1
Supervised machine learning (ML) algorithms have recently been proposed as an alternative to traditional tractography methods in order to address some of their weaknesses. They can…
Within-Brain Classification for Brain Tumor Segmentation
Mohammad Havaei, Hugo Larochelle, Philippe Poulin +1
Purpose: In this paper, we investigate a framework for interactive brain tumor segmentation which, at its core, treats the problem of interactive brain tumor segmentation as a mach…