28 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Université de MontréalCA20 papers
- Polytechnique MontréalCA12 papers
- École de Technologie SupérieureCA7 papers
- Mila - Quebec Artificial Intelligence InstituteCA7 papers
- CHU Sainte-Justine Research CenterCA5 papers
- Centre National de la Recherche ScientifiqueFR4 papers
- Laboratoire de traitement de l'information en santé4 papers
- Palacký University OlomoucCZ3 papers
- University of WashingtonUS3 papers
- CentraleSupélecFR2 papers
- Max Planck Institute for Human Cognitive and Brain SciencesDE2 papers
- Université Paris-SaclayFR2 papers
25 papers
Segmentation of spinal rootlets across MRI contrasts with RootletSeg
Katerina Krejci, Jiri Chmelik, Sandrine Bedard +5
Purpose: To develop a deep learning method for the automatic segmentation of spinal nerve rootlets on various MRI scans. Material and Methods: This retrospective study included MRI…
Unpaired Modality Translation for Pseudo Labeling of Histology Images
Arthur Boschet, Armand Collin, Nishka Katoch +1
The segmentation of histological images is critical for various biomedical applications, yet the lack of annotated data presents a significant challenge. We propose a microscopy ps…
Development and Comparative Analysis of Machine Learning Models for Hypoxemia Severity Triage in CBRNE Emergency Scenarios Using Physiological and Demographic Data from Medical-Grade Devices
Santino Nanini, Mariem Abid, Yassir Mamouni +3
This paper presents the development of machine learning (ML) models to predict hypoxemia severity during emergency triage, especially in Chemical, Biological, Radiological, Nuclear…
SCIsegV2: A Universal Tool for Segmentation of Intramedullary Lesions in Spinal Cord Injury
Enamundram Naga Karthik, Jan Valošek, Lynn Farner +10
Spinal cord injury (SCI) is a devastating incidence leading to permanent paralysis and loss of sensory-motor functions potentially resulting in the formation of lesions within the…
Harmonizing Flows: Leveraging normalizing flows for unsupervised and source-free MRI harmonization
Farzad Beizaee, Gregory A. Lodygensky, Chris L. Adamson +5
Lack of standardization and various intrinsic parameters for magnetic resonance (MR) image acquisition results in heterogeneous images across different sites and devices, which adv…
The Impact of LoRA Adapters on LLMs for Clinical Text Classification Under Computational and Data Constraints
Thanh-Dung Le, Ti Ti Nguyen, Vu Nguyen Ha +3
Fine-tuning Large Language Models (LLMs) for clinical Natural Language Processing (NLP) poses significant challenges due to domain gap, limited data, and stringent hardware constra…
Impact of Initialization on Intra-subject Pediatric Brain MR Image Registration: A Comparative Analysis between SyN ANTs and Deep Learning-Based Approaches
Andjela Dimitrijevic, Vincent Noblet, Benjamin De Leener
This study evaluates the performance of conventional SyN ANTs and learning-based registration methods in the context of pediatric neuroimaging, specifically focusing on intrasubjec…
Automatic Segmentation of the Spinal Cord Nerve Rootlets
Jan Valosek, Theo Mathieu, Raphaelle Schlienger +2
Precise identification of spinal nerve rootlets is relevant to delineate spinal levels for the study of functional activity in the spinal cord. The goal of this study was to develo…
From Physics to Sentience: Deciphering the Semantics of the Free-Energy Principle and Evaluating its Claims
Zahra Sheikhbahaee, Adam Safron, Casper Hesp +1
The Free-Energy Principle (FEP) [1-3] has been adopted in a variety of ambitious proposals that aim to characterize all adaptive, sentient, and cognitive systems within a unifying…
A Novel Transformer-Based Self-Supervised Learning Method to Enhance Photoplethysmogram Signal Artifact Detection
Thanh-Dung Le, Clara Macabiau, Kévin Albert +2
Recent research at CHU Sainte Justine's Pediatric Critical Care Unit (PICU) has revealed that traditional machine learning methods, such as semi-supervised label propagation and K-…
Label Propagation Techniques for Artifact Detection in Imbalanced Classes using Photoplethysmogram Signals
Clara Macabiau, Thanh-Dung Le, Kevin Albert +3
This study aimed to investigate the application of label propagation techniques to propagate labels among photoplethysmogram (PPG) signals, particularly in imbalanced class scenari…
Improving Transformer Performance for French Clinical Notes Classification Using Mixture of Experts on a Limited Dataset
Thanh-Dung Le, Philippe Jouvet, Rita Noumeir
Transformer-based models have shown outstanding results in natural language processing but face challenges in applications like classifying small-scale clinical texts, especially w…
Direct multiple shooting and direct collocation perform similarly in biomechanical predictive simulations
P. Puchaud, F. Bailly, M. Begon
Direct multiple shooting (DMS) and direct collocation (DC) are two common transcription methods for solving optimal control problems (OCP) in biomechanics and robotics. They have r…
Dynamic Shimming in the Cervical Spinal Cord for Multi-Echo Gradient-Echo Imaging at 3 T
E. Alonso-Ortiz, D. Papp, A. D'Astous +1
Obtaining high quality images of the spinal cord with MRI is difficult, partly due to the fact that the spinal cord is surrounded by a number of structures that have differing magn…
Detecting of a Patient's Condition From Clinical Narratives Using Natural Language Representation
Thanh-Dung Le, Rita Noumeir, Jerome Rambaud +2
The rapid progress in clinical data management systems and artificial intelligence approaches enable the era of personalized medicine. Intensive care units (ICUs) are the ideal cli…
Three-dimensional Segmentation of the Scoliotic Spine from MRI using Unsupervised Volume-based MR-CT Synthesis
Enamundram M. V. Naga Karthik, Catherine Laporte, Farida Cheriet
Vertebral bone segmentation from magnetic resonance (MR) images is a challenging task. Due to the inherent nature of the modality to emphasize soft tissues of the body, common thre…
Conditional canonical correlation estimation based on covariates with random forests
Cansu Alakus, Denis Larocque, Sebastien Jacquemont +5
Investigating the relationships between two sets of variables helps to understand their interactions and can be done with canonical correlation analysis (CCA). However, the correla…
End-to-End Deep Learning Model for Cardiac Cycle Synchronization from Multi-View Angiographic Sequences
Raphaël Royer-Rivard, Fantin Girard, Nagib Dahdah +1
Dynamic reconstructions (3D+T) of coronary arteries could give important perfusion details to clinicians. Temporal matching of the different views, which may not be acquired simult…
Recording and manipulation of vagus nerve electrical activity in chronically instrumented unanesthetized near term fetal sheep
Aude Castel, Patrick M. Burns, Javier Benito +9
Background: The chronically instrumented pregnant sheep has been used as a model of human fetal development and responses to pathophysiologic stimuli. This is due to the unique ame…
Vagal contributions to fetal heart rate variability: an omics approach
Christophe L. Herry, Patrick Burns, Andre Desrochers +5
Fetal heart rate variability (fHRV) is an important indicator of health and disease, yet its physiological origins, neural contributions in particular, are not well understood. We…
Alpha7 nicotinic acetylcholine receptor signaling modulates ovine fetal brain astrocytes transcriptome in response to endotoxin
M. Cao, J. W. MacDonald, H. L. Liu +12
Neuroinflammation in utero may result in lifelong neurological disabilities. Astrocytes play a pivotal role, but the mechanisms are poorly understood. No early postnatal treatment…
Dilatation of Lateral Ventricles with Brain Volumes in Infants with 3D Transfontanelle US
Marc-Antoine Boucher, Sarah Lippe, Amelie Damphousse +2
Ultrasound (US) can be used to assess brain development in newborns, as MRI is challenging due to immobilization issues, and may require sedation. Dilatation of the lateral ventric…
Spatiotemporal Manifold Prediction Model for Anterior Vertebral Body Growth Modulation Surgery in Idiopathic Scoliosis
William Mandel, Olivier Turcot, Dejan Knez +2
Anterior Vertebral Body Growth Modulation (AVBGM) is a minimally invasive surgical technique that gradually corrects spine deformities while preserving lumbar motion. However the s…
Prior-based Coregistration and Cosegmentation
Mahsa Shakeri, Enzo Ferrante, Stavros Tsogkas +4
We propose a modular and scalable framework for dense coregistration and cosegmentation with two key characteristics: first, we substitute ground truth data with the semantic map o…