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
6 papers · 1 filter
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…