527 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Université de MontréalCA8 papers
- Polytechnique MontréalCA5 papers
- Harvard UniversityUS3 papers
- McGill UniversityCA3 papers
- Charité - Universitätsmedizin BerlinDE2 papers
- École de Technologie SupérieureCA2 papers
- Jewish General HospitalCA2 papers
- Universitat Pompeu FabraES2 papers
- Université du QuébecCA2 papers
- University College LondonGB2 papers
- AGH University of KrakowPL1 paper
- Athinoula A. Martinos Center for Biomedical ImagingUS1 paper
17 papers
Neu-RadBERT for Enhanced Diagnosis of Brain Injuries and Conditions
Manpreet Singh, Sean Macrae, Pierre-Marc Williams +6
Objective: We sought to develop a classification algorithm to extract diagnoses from free-text radiology reports of brain imaging performed in patients with acute respiratory failu…
Transfer Learning and Machine Learning for Training Five Year Survival Prognostic Models in Early Breast Cancer
Lisa Pilgram, Kai Yang, Ana-Alicia Beltran-Bless +22
Prognostic information is essential for decision-making in breast cancer management. Recently trials have predominantly focused on genomic prognostication tools, even though clinic…
RetinaVR: Democratizing Vitreoretinal Surgery Training with a Portable and Affordable Virtual Reality Simulator in the Metaverse
Fares Antaki, Cédryk Doucet, Daniel Milad +3
We developed and validated RetinaVR, an affordable and immersive virtual reality simulator for vitreoretinal surgery training, using the Meta Quest 2 VR headset. We focused on four…
The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography
Kaiyuan Yang, Fabio Musio, Yihui Ma +112
The Circle of Willis (CoW) is an important network of arteries connecting major circulations of the brain. Its vascular architecture is believed to influence the risk, severity, an…
Personalised dynamic super learning: an application in predicting hemodiafiltration convection volumes
Arthur Chatton, Michèle Bally, Renée Lévesque +3
Obtaining continuously updated predictions is a major challenge for personalised medicine. Leveraging combinations of parametric regressions and machine learning approaches, the pe…
A Foundation Language-Image Model of the Retina (FLAIR): Encoding Expert Knowledge in Text Supervision
Julio Silva-Rodríguez, Hadi Chakor, Riadh Kobbi +2
Foundation vision-language models are currently transforming computer vision, and are on the rise in medical imaging fueled by their very promising generalization capabilities. How…
Towards Foundation Models and Few-Shot Parameter-Efficient Fine-Tuning for Volumetric Organ Segmentation
Julio Silva-Rodríguez, Jose Dolz, Ismail Ben Ayed
The recent popularity of foundation models and the pre-train-and-adapt paradigm, where a large-scale model is transferred to downstream tasks, is gaining attention for volumetric m…
Contextual guidance: An integrated theory for astrocytes function in brain circuits and behavior
Ciaran Murphy-Royal, ShiNung Ching, Thomas Papouin
The participation of astrocytes in brain computation was formally hypothesized in 1992, coinciding with the discovery that these glial cells display a complex form of Ca2+ excitabi…
Segmentation with mixed supervision: Confidence maximization helps knowledge distillation
Bingyuan Liu, Christian Desrosiers, Ismail Ben Ayed +1
Despite achieving promising results in a breadth of medical image segmentation tasks, deep neural networks require large training datasets with pixel-wise annotations. Obtaining th…
Do We Really Need Dice? The Hidden Region-Size Biases of Segmentation Losses
Bingyuan Liu, Jose Dolz, Adrian Galdran +2
Most segmentation losses are arguably variants of the Cross-Entropy (CE) or Dice losses. On the surface, these two categories of losses seem unrelated, and there is no clear consen…
Evaluation of MRI to ultrasound registration methods for brain shift correction: The CuRIOUS2018 Challenge
Yiming Xiao, Hassan Rivaz, Matthieu Chabanas +13
In brain tumor surgery, the quality and safety of the procedure can be impacted by intra-operative tissue deformation, called brain shift. Brain shift can move the surgical targets…
Multi-Level Batch Normalization In Deep Networks For Invasive Ductal Carcinoma Cell Discrimination In Histopathology Images
Francisco Perdigon Romero, An Tang, Samuel Kadoury
Breast cancer is the most diagnosed cancer and the most predominant cause of death in women worldwide. Imaging techniques such as the breast cancer pathology helps in the diagnosis…
Boundary loss for highly unbalanced segmentation
Hoel Kervadec, Jihene Bouchtiba, Christian Desrosiers +3
Widely used loss functions for CNN segmentation, e.g., Dice or cross-entropy, are based on integrals over the segmentation regions. Unfortunately, for highly unbalanced segmentatio…
Microfluidic multipoles: theory and applications
Pierre-Alexandre Goyette, Étienne Boulais, Frédéric Normandeau +3
Microfluidic multipoles (MFMs) have been realized experimentally and hold promise for "open-space" biological and chemical surface processing. Whereas convective flow can readily b…
Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer
Martin Vallières, Emily Kay-Rivest, Léo Jean Perrin +9
Quantitative extraction of high-dimensional mineable data from medical images is a process known as radiomics. Radiomics is foreseen as an essential prognostic tool for cancer risk…
Planetary systems and real planetary nebulae from planet destruction near white dwarfs
Ealeal Bear, Noam Soker
We suggest that tidal destruction of Earth-like and icy planets near a white dwarf (WD) might lead to the formation of one or more low-mass - Earth-like and lighter - planets in ti…
GPUMCD: a new GPU-oriented Monte Carlo dose calculation platform
Sami Hissoiny, Hugo Bouchard, Benoît Ozell +1
Purpose: Monte Carlo methods are considered the gold standard for dosimetric computations in radiotherapy. Their execution time is however still an obstacle to the routine use of M…