Ismail Ben Ayed, Université de Montréal

Research

Artificial Intelligence Intracerebral Hemorrhage Outcome Prediction Segmentation Stroke

Latest papers

Deep Learning Models Connecting Images and Text: A Primer for Radiologists.
Radiographics : a review publication of the Radiological Society of North America, Inc · 2025
Source-free domain adaptation for image segmentation.
Medical image analysis · 2022 · senior author
Annotation-efficient deep learning for automatic medical image segmentation.
Nature communications · 2021

All 11 publications

Latest funding

Enhancing Robustness in Non-Contrast CT Image Analysis for Stroke: Application to Intracerebral Hemorrhage Outcome Prediction
CIHR · 2025 · Principal investigator
$405,451
Prize - 202109PJT - Artificial Intelligence to Monitor Radiotherapy Efficacy and Complications through Imaging Technology (AI-REACT)
CIHR · 2021 · Co-investigator
$25,000
Artificial Intelligence to Monitor Radiotherapy Efficacy and Complications through Imaging Technology (AI-REACT)
CIHR · 2021 · Co-investigator
$229,500

All 3 grants and awards

11 publications.

01

Deep Learning Models Connecting Images and Text: A Primer for Radiologists.

Wu AN, Kulbay M, Cheng PM, Cadrin-Chênevert A, Létourneau-Guillon L, Chartrand G, Chong J, Montagnon E, Ben Ayed I, Tang A

Radiographics : a review publication of the Radiological Society of North America, Inc2025

DOI: 10.1148/rg.240103 PMID: 40811083

02

Source-free domain adaptation for image segmentation.

Bateson M, Kervadec H, Dolz J, Lombaert H, Ben Ayed I

Medical image analysis2022Senior author

DOI: 10.1016/j.media.2022.102617 PMID: 36228364

03

Annotation-efficient deep learning for automatic medical image segmentation.

Wang S, Li C, Wang R, Liu Z, Wang M, Tan H, Wu Y, Liu X, Sun H, Yang R, Liu X, Chen J, Zhou H, Ben Ayed I, Zheng H

Nature communications2021

DOI: 10.1038/s41467-021-26216-9 PMID: 34625565

04

Boundary loss for highly unbalanced segmentation.

Kervadec H, Bouchtiba J, Desrosiers C, Granger E, Dolz J, Ben Ayed I

Medical image analysis2021Senior author

DOI: 10.1016/j.media.2020.101851 PMID: 33080507

05

Discretely-constrained deep network for weakly supervised segmentation.

Peng J, Kervadec H, Dolz J, Ben Ayed I, Pedersoli M, Desrosiers C

Neural networks : the official journal of the International Neural Network Society2020

DOI: 10.1016/j.neunet.2020.07.011 PMID: 32721843

06

Non-uniform Label Smoothing for Diabetic Retinopathy Grading from Retinal Fundus Images with Deep Neural Networks.

Galdran A, Chelbi J, Kobi R, Dolz J, Lombaert H, Ben Ayed I, Chakor H

Translational vision science & technology2020

DOI: 10.1167/tvst.9.2.34 PMID: 32832207

07

Deep CNN ensembles and suggestive annotations for infant brain MRI segmentation.

Dolz J, Desrosiers C, Wang L, Yuan J, Shen D, Ben Ayed I

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society2020Senior author

DOI: 10.1016/j.compmedimag.2019.101660 PMID: 31785402

08

Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images.

Carass A, Cuzzocreo JL, Han S, Hernandez-Castillo CR, Rasser PE, Ganz M, Beliveau V, Dolz J, Ben Ayed I, Desrosiers C, Thyreau B, Romero JE, Coupé P, Manjón JV, Fonov VS, Collins DL, Ying SH, Onyike CU, Crocetti D, Landman BA, Mostofsky SH, Thompson PM, Prince JL

NeuroImage2018

DOI: 10.1016/j.neuroimage.2018.08.003 PMID: 30099076

09

3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study.

Dolz J, Desrosiers C, Ben Ayed I

NeuroImage2018Senior author

DOI: 10.1016/j.neuroimage.2017.04.039 PMID: 28450139

10

Spine labeling in axial magnetic resonance imaging via integral kernels.

Miles B, Ben Ayed I, Hojjat SP, Wang MH, Li S, Fenster A, Garvin GJ

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society2016

DOI: 10.1016/j.compmedimag.2016.09.004 PMID: 27743641

Enhancing Robustness in Non-Contrast CT Image Analysis for Stroke: Application to Intracerebral Hemorrhage Outcome Prediction

Principal investigatorCIHR2025Project Grant

Principal investigators: Létourneau Guillon, Laurent; Aviv, Richard; Ben Ayed, Ismail; Dolz, Jose; Gioia, Laura C

Keywords: Artificial Intelligence; Intracerebral Hemorrhage; Outcome Prediction; Segmentation; Stroke

$405,451

Prize - 202109PJT - Artificial Intelligence to Monitor Radiotherapy Efficacy and Complications through Imaging Technology (AI-REACT)

Co-investigatorCIHR2021PRIZE - Project Grant - PA: Prize: Early Career Investigator in Cancer

Principal investigators: Bahig, Houda

Keywords: Artificial Intelligence; Cancer Control; Delta-Radiomics; Head And Neck Cancer; Machine Learning; Prediction; Toxicity

$25,000

Artificial Intelligence to Monitor Radiotherapy Efficacy and Complications through Imaging Technology (AI-REACT)

Co-investigatorCIHR2021Project Grant

Principal investigators: Bahig, Houda

Keywords: Artificial Intelligence; Cancer Control; Delta-Radiomics; Head And Neck Cancer; Machine Learning; Prediction; Toxicity

$229,500

From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.

Frequent collaborators

Radiologie
John P. Robarts Research Institute
Diagnostic Radiology
Medicine
Other

Co-authors at Université de Montréal, colored by department. Thicker lines mean more shared papers; select anyone to open their profile and their own map.

Jose Dolz

Radiologie

6 shared papers, latest 2022

An Tang

Diagnostic Radiology

1 shared papers, latest 2025

Aaron Fenster

John P. Robarts Research Institute

1 shared papers, latest 2016

Pierre Boulanger

Medicine

1 shared papers, latest 2016

Harald Becher

Faculty

1 shared papers, latest 2016

Write to this professor

A short, specific email works best. This draft uses one of their recent papers; replace the parts in brackets with your own details before sending.

Applying for

Paper to mentionMention their CIHR grant from 2025

Subject: Prospective PhD student: Artificial Intelligence Dear Professor Ben Ayed, My name is [your name], and I am a [your current degree or role] at [your institution]. I am applying for a PhD position starting in [term and year]. I read your paper "Deep Learning Models Connecting Images and Text: A Primer for Radiologists." (2025), and it connects closely to my own work on [your research topic]. [One or two sentences on what you did and what you learned.] I also saw your CIHR-funded project "Enhancing Robustness in Non-Contrast CT Image Analysis for Stroke: Application to Intracerebral Hemorrhage Outcome Prediction" (2025), and I would be glad to contribute to work in that direction. Are you accepting new PhD students for [term and year]? I have attached my CV and transcripts, and I would be glad to talk at a time that suits you. Thank you for your time. Kind regards, [your name]