13 citations · 37 across the 14 of their papers we have counts for
5 papers · 1 filter
Monte Carlo dropout increases model repeatability
Andreanne Lemay, Katharina Hoebel, Christopher P. Bridge +5
The integration of artificial intelligence into clinical workflows requires reliable and robust models. Among the main features of robustness is repeatability. Much attention is gi…
Team NeuroPoly: Description of the Pipelines for the MICCAI 2021 MS New Lesions Segmentation Challenge
Uzay Macar, Enamundram Naga Karthik, Charley Gros +2
This paper gives a detailed description of the pipelines used for the 2nd edition of the MICCAI 2021 Challenge on Multiple Sclerosis Lesion Segmentation. An overview of the data pr…
Fair Conformal Predictors for Applications in Medical Imaging
Charles Lu, Andreanne Lemay, Ken Chang +2
Deep learning has the potential to automate many clinically useful tasks in medical imaging. However translation of deep learning into clinical practice has been hindered by issues…
Evaluating subgroup disparity using epistemic uncertainty in mammography
Charles Lu, Andreanne Lemay, Katharina Hoebel +1
As machine learning (ML) continue to be integrated into healthcare systems that affect clinical decision making, new strategies will need to be incorporated in order to effectively…
Benefits of Linear Conditioning with Metadata for Image Segmentation
Andreanne Lemay, Charley Gros, Olivier Vincent +3
Medical images are often accompanied by metadata describing the image (vendor, acquisition parameters) and the patient (disease type or severity, demographics, genomics). This meta…