Andréanne Lemay

According to our database, Andréanne Lemay authored at least 14 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2023

A generalized framework to predict continuous scores from medical ordinal labels.

Katharina Viktoria Hoebel, Andréanne Lemay, John Peter Campbell, Susan Ostmo, Michael F. Chiang, Christopher P. Bridge, Matthew D. Li, Praveer Singh, Aaron S. Coyner, Jayashree Kalpathy-Cramer

CoRR, 2023

2022

Improving the repeatability of deep learning models with Monte Carlo dropout.

Andréanne Lemay, Katharina Hoebel, Christopher P. Bridge, Brian Befano, Silvia De Sanjosé, Didem Egemen, Ana Cecilia Rodriguez, Mark Schiffman, John Peter Campbell, Jayashree Kalpathy-Cramer

npj Digit. Medicine, 2022

Label fusion and training methods for reliable representation of inter-rater uncertainty.

Andréanne Lemay, Charley Gros, Julien Cohen-Adad

CoRR, 2022

Do I know this? segmentation uncertainty under domain shift.

Katharina Hoebel, Christopher P. Bridge, Andréanne Lemay, Ken Chang, Jay B. Patel, Bruce Rosen, Jayashree Kalpathy-Cramer

Proceedings of the Medical Imaging 2022: Image Processing, 2022

Fair Conformal Predictors for Applications in Medical Imaging.

Charles Lu, Andréanne Lemay, Ken Chang, Katharina Höbel, Jayashree Kalpathy-Cramer

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

SoftSeg: Advantages of soft versus binary training for image segmentation.

Charley Gros, Andréanne Lemay, Julien Cohen-Adad

Medical Image Anal., 2021

ivadomed: A Medical Imaging Deep Learning Toolbox.

Charley Gros, Andréanne Lemay, Olivier Vincent, Lucas Rouhier, Marie-Helene Bourget, Anthime Bucquet, Joseph Paul Cohen, Julien Cohen-Adad

J. Open Source Softw., 2021

Monte Carlo dropout increases model repeatability.

Andréanne Lemay, Katharina Hoebel, Christopher P. Bridge, Didem Egemen, Ana Cecilia Rodriguez, Mark Schiffman, John Peter Campbell, Jayashree Kalpathy-Cramer

CoRR, 2021

Team NeuroPoly: Description of the Pipelines for the MICCAI 2021 MS New Lesions Segmentation Challenge.

Uzay Macar, Enamundram Naga Karthik, Charley Gros, Andréanne Lemay, Julien Cohen-Adad

CoRR, 2021

Evaluating subgroup disparity using epistemic uncertainty in mammography.

Charles Lu, Andréanne Lemay, Katharina Hoebel, Jayashree Kalpathy-Cramer

CoRR, 2021

Benefits of Linear Conditioning for Segmentation using Metadata.

Andréanne Lemay, Charley Gros, Olivier Vincent, Yaou Liu, Joseph Paul Cohen, Julien Cohen-Adad

Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021

2020

Multiclass Spinal Cord Tumor Segmentation on MRI with Deep Learning.

Andréanne Lemay, Charley Gros, Zhizheng Zhuo, Jie Zhang, Yunyun Duan, Julien Cohen-Adad, Yaou Liu

CoRR, 2020

ivadomed: A Medical Imaging Deep Learning Toolbox.

Charley Gros, Andréanne Lemay, Olivier Vincent, Lucas Rouhier, Anthime Bucquet, Joseph Paul Cohen, Julien Cohen-Adad

CoRR, 2020

2019

Kidney Recognition in CT Using YOLOv3.

Andréanne Lemay

CoRR, 2019