469 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of TorontoCA29 papers
- Sunnybrook Research Institute11 papers
- University of WaterlooCA9 papers
- Health Sciences CentreCA8 papers
- McGill UniversityCA5 papers
- University College LondonGB5 papers
- University Health NetworkCA5 papers
- Imperial College LondonGB4 papers
- InsermFR4 papers
- Sunnybrook HospitalCA4 papers
- University of AlbertaCA4 papers
- University of British ColumbiaCA4 papers
38 papers
The MYOSAIQ Challenge: Myocardial Segmentation with Automated Infarct Quantification
Olivier Bernard, William A. Romero R., Cyprien Bouton +24
Late gadolinium enhancement (LGE) cardiac magnetic resonance (MR) imaging is the modality of choice to assess myocardial infarction (MI) lesions. Nowadays MI volume quantification…
Towards patient-specific optimization for mandibular reconstruction planning based on predicted bone-union propensity
Hamidreza Aftabi, John E. Lloyd, Amanda Ding +4
Mandibular reconstruction with vascularized bone grafts is complicated by donor-host nonunion, and virtual surgical planning produces a geometric plan rather than optimizing for bo…
Development and pilot evaluation of a virtual reality simulator for HDR prostate brachytherapy
Anton Varlukhin, Mackenzie Smith, Fahad Alam +8
Purpose: To develop a virtual reality simulator for high dose rate prostate brachytherapy and to test whether participation is associated with immediate gains in self-reported conf…
A generalizable 3D framework and model for self-supervised learning in medical imaging
Tony Xu, Sepehr Hosseini, Chris Anderson +4
Current self-supervised learning methods for 3D medical imaging rely on simple pretext formulations and organ- or modality-specific datasets, limiting their generalizability and sc…
Mamba-based Deep Learning Approach for Sleep Staging on a Wireless Multimodal Wearable System without Electroencephalography
Andrew H. Zhang, Alex He-Mo, Richard Fei Yin +9
Study Objectives: We investigate a Mamba-based deep learning approach for sleep staging on signals from ANNE One (Sibel Health, Evanston, IL), a non-intrusive dual-module wireless…
The Canadian VirusSeq Data Portal & Duotang: open resources for SARS-CoV-2 viral sequences and genomic epidemiology
Erin E. Gill, Baofeng Jia, Carmen Lia Murall +67
The COVID-19 pandemic led to a large global effort to sequence SARS-CoV-2 genomes from patient samples to track viral evolution and inform public health response. Millions of SARS-…
A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge
Ezequiel de la Rosa, Mauricio Reyes, Sook-Lei Liew +55
Diffusion-weighted MRI (DWI) is essential for stroke diagnosis, treatment decisions, and prognosis. However, image and disease variability hinder the development of generalizable A…
Current Methods for Hyperpolarized [1-13C]pyruvate MRI Human Studies
Peder EZ Larson, Jenna ML Bernard, James A Bankson +16
MRI with hyperpolarized (HP) 13C agents, also known as HP 13C MRI, can measure processes such as localized metabolism that is altered in numerous cancers, liver, heart, kidney dise…
Mitigating Aberration-Induced Noise: A Deep Learning-Based Aberration-to-Aberration Approach
Mostafa Sharifzadeh, Sobhan Goudarzi, An Tang +2
One of the primary sources of suboptimal image quality in ultrasound imaging is phase aberration. It is caused by spatial changes in sound speed over a heterogeneous medium, which…
Automated Whole Slide Imaging for Label-Free Histology using Photon Absorption Remote Sensing Microscopy
James E. D. Tweel, Benjamin R. Ecclestone, Marian Boktor +3
The field of histology relies heavily on antiquated tissue processing and staining techniques that limit the efficiency of pathologic diagnoses of cancer and other diseases. Curren…
SF2Former: Amyotrophic Lateral Sclerosis Identification From Multi-center MRI Data Using Spatial and Frequency Fusion Transformer
Rafsanjany Kushol, Collin C. Luk, Avyarthana Dey +15
Amyotrophic Lateral Sclerosis (ALS) is a complex neurodegenerative disorder involving motor neuron degeneration. Significant research has begun to establish brain magnetic resonanc…
Understanding metric-related pitfalls in image analysis validation
Annika Reinke, Minu D. Tizabi, Michael Baumgartner +75
Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation int…
Metrics reloaded: Recommendations for image analysis validation
Lena Maier-Hein, Annika Reinke, Patrick Godau +71
Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen…
Measuring hand use in the home after cervical spinal cord injury using egocentric video
Andrea Bandini, Mehdy Dousty, Sander L. Hitzig +3
Background: Egocentric video has recently emerged as a potential solution for monitoring hand function in individuals living with tetraplegia in the community, especially for its a…
BI-RADS BERT & Using Section Segmentation to Understand Radiology Reports
Grey Kuling, Belinda Curpen, Anne L. Martel
Radiology reports are one of the main forms of communication between radiologists and other clinicians and contain important information for patient care. In order to use this info…
Probeable DARTS with Application to Computational Pathology
Sheyang Tang, Mahdi S. Hosseini, Lina Chen +5
AI technology has made remarkable achievements in computational pathology (CPath), especially with the help of deep neural networks. However, the network performance is highly rela…
Adapting to Unseen Vendor Domains for MRI Lesion Segmentation
Brandon Mac, Alan R. Moody, April Khademi
One of the key limitations in machine learning models is poor performance on data that is out of the domain of the training distribution. This is especially true for image analysis…
COVID-Rate: An Automated Framework for Segmentation of COVID-19 Lesions from Chest CT Scans
Nastaran Enshaei, Anastasia Oikonomou, Moezedin Javad Rafiee +5
Novel Coronavirus disease (COVID-19) is a highly contagious respiratory infection that has had devastating effects on the world. Recently, new COVID-19 variants are emerging making…
An optimal control approach to determine resistance-type boundary conditions from in-vivo data for cardiovascular simulations
Elisa Fevola, Francesco Ballarin, Laura Jiménez-Juan +4
The choice of appropriate boundary conditions is a fundamental step in computational fluid dynamics (CFD) simulations of the cardiovascular system. Boundary conditions, in fact, hi…
Self-supervised driven consistency training for annotation efficient histopathology image analysis
Chetan L. Srinidhi, Seung Wook Kim, Fu-Der Chen +1
Training a neural network with a large labeled dataset is still a dominant paradigm in computational histopathology. However, obtaining such exhaustive manual annotations is often…
Estimating Uncertainty in Neural Networks for Cardiac MRI Segmentation: A Benchmark Study
Matthew Ng, Fumin Guo, Labonny Biswas +4
Objective: Convolutional neural networks (CNNs) have demonstrated promise in automated cardiac magnetic resonance image segmentation. However, when using CNNs in a large real-world…
Essential requirements for establishing and operating data trusts: practical guidance based on a working meeting of fifteen Canadian organizations and initiatives
P. Alison Paprica, Eric Sutherland, Andrea Smith +11
Introduction: Increasingly, the label data trust is being applied to repeatable mechanisms or approaches to sharing data in a timely, fair, safe and equitable way. However, there i…
Reduced order methods for parametric optimal flow control in coronary bypass grafts, towards patient-specific data assimilation
Zakia Zainib, Francesco Ballarin, Stephen Fremes +3
Coronary artery bypass grafts (CABG) surgery is an invasive procedure performed to circumvent partial or complete blood flow blockage in coronary artery disease (CAD). In this work…
Improving Prognostic Performance in Resectable Pancreatic Ductal Adenocarcinoma using Radiomics and Deep Learning Features Fusion in CT Images
Yucheng Zhang, Edrise M. Lobo-Mueller, Paul Karanicolas +3
As an analytic pipeline for quantitative imaging feature extraction and analysis, radiomics has grown rapidly in the past a few years. Recent studies in radiomics aim to investigat…