Hassan Rivaz, Concordia University

Research

Breast Cancer Deep Learning Explainable Ai Lymphedema Machine Learning Ultrasound Imaging

Latest papers

Deep learning-based femoral reconstruction from intraoperative point clouds for enhanced knee arthroplasty registration.
International journal of computer assisted radiology and surgery · 2026 · senior author
Statistical shape model-based estimation of registration error in computer-assisted total knee arthroplasty.
International journal of computer assisted radiology and surgery · 2026 · senior author
Characterizing forearm skeletal muscle composition and function in breast cancer-related lymphedema using B-mode ultrasonography.
Clinical physiology and functional imaging · 2026

All 52 publications

Latest funding

Accessible Diagnosis and Staging of Breast Cancer-Related Lymphedema with AI-Powered Point of Care Ultrasound
CIHR · 2026 · Nominated PI
$100,000
Accessible Diagnosis and Staging of Breast Cancer-Related Lymphedema with AI-Powered Point of Care Ultrasound
CIHR · 2025 · Nominated PI
$100,000
Improved Total Knee Arthroplasty Registration Using Deep Learning and Ultrasound
NSERC · 2024 · Principal investigator
$40,000

All 14 grants and awards

52 publications.

01

Deep learning-based femoral reconstruction from intraoperative point clouds for enhanced knee arthroplasty registration.

Kafian Safari M, Mirzae M, Gheflati B, Sharifzade M, Zuhars J, Rottoo S, Rivaz H

International journal of computer assisted radiology and surgery2026Senior author

DOI: 10.1007/s11548-026-03609-z PMID: 41984365

02

Statistical shape model-based estimation of registration error in computer-assisted total knee arthroplasty.

Gheflati B, Mirzaei M, Zuhars J, Rottoo S, Rivaz H

International journal of computer assisted radiology and surgery2026Senior author

DOI: 10.1007/s11548-025-03566-z PMID: 41495592

03

Characterizing forearm skeletal muscle composition and function in breast cancer-related lymphedema using B-mode ultrasonography.

Whyte J, Towers A, Boily M, Rosenthall L, Rivaz H, Kilgour RD

Clinical physiology and functional imaging2026

DOI: 10.1111/cpf.70051 PMID: 41674486

04

MedCLIP-SAMv2: Towards universal text-driven medical image segmentation.

Koleilat T, Asgariandehkordi H, Rivaz H, Xiao Y

Medical image analysis2025

DOI: 10.1016/j.media.2025.103749 PMID: 40779830

05

Deformable detection transformers for domain adaptable ultrasound localization microscopy with robustness to point spread function variations.

Gharamaleki SK, Helfield B, Rivaz H

Scientific reports2025Senior author

DOI: 10.1038/s41598-025-09120-w PMID: 40640235

06

Joint enhancement of automatic chest x-ray diagnosis and radiological gaze prediction with multistage cooperative learning.

Qiu Z, Rivaz H, Xiao Y

Medical physics2025

DOI: 10.1002/mp.17977 PMID: 40665596

07

Ultrasound and MRI-based evaluation of relationships between morphological and mechanical properties of the lower lumbar multifidus muscle in chronic low back pain.

Naghdi N, Masi S, Bertrand C, Rosenstein B, Cohen-Adad J, Rivaz H, Roy M, Fortin M

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2025

DOI: 10.1007/s00586-025-09012-7 PMID: 40488869

08

CASCADE-FSL: Few-shot learning for collateral evaluation in ischemic stroke.

Aktar M, Tampieri D, Xiao Y, Rivaz H, Kersten-Oertel M

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society2025

DOI: 10.1016/j.compmedimag.2025.102550 PMID: 40250214

09

Leveraging deep learning for nonlinear shape representation in anatomically parameterized statistical shape models.

Gheflati B, Mirzaei M, Rottoo S, Rivaz H

International journal of computer assisted radiology and surgery2025Senior author

DOI: 10.1007/s11548-025-03330-3 PMID: 39953355

10

Ultrasound Segmentation Using Semi-Supervised Learning: Application in Point-of-Care Sarcopenia Assessment.

Rasaee H, Samuel M, Behboodi B, Afilalo J, Rivaz H

IEEE open journal of engineering in medicine and biology2025Senior author

DOI: 10.1109/ojemb.2025.3537560 PMID: 40635998

Accessible Diagnosis and Staging of Breast Cancer-Related Lymphedema with AI-Powered Point of Care Ultrasound

Nominated PICIHR2026PJT PA: ICR - Lev. AI to trans. canc. rese. - AI to accel. Breast Can. Research

Principal investigators: Rivaz, Hassan

Keywords: Breast Cancer; Deep Learning; Explainable Ai; Lymphedema; Machine Learning; Ultrasound Imaging

$100,000

Accessible Diagnosis and Staging of Breast Cancer-Related Lymphedema with AI-Powered Point of Care Ultrasound

Nominated PICIHR2025Project Grant - Priority Announcement - Breast Cancer Survivorship

Principal investigators: Rivaz, Hassan

Keywords: Breast Cancer; Deep Learning; Explainable Ai; Lymphedema; Machine Learning; Ultrasound Imaging

$100,000

Improved Total Knee Arthroplasty Registration Using Deep Learning and Ultrasound

Principal investigatorNSERC2024Alliance Grants

Principal investigators: Rivaz, Hassan H

Keywords: computer integrated surgery; deep learning; image processing; machine learning; medical imaging; medical robotics; registration; ultrasound imaging

$40,000

Quantitative ultrasound to improve detection and diagnosis of liver cancer

Co-investigatorCIHR2023Project Grant

Principal investigators: Tang, An; Cloutier, Guy

Keywords: Diagnosis; Diagnostic Performance; Elastography; Hepatocellular Carcinoma; Liver Cancer; Quantitative Ultrasound (Qus); Screening; Surveillance; Ultrasound; Viscoelastography

$1,014,120

Unsupervised deep learning for ultrasound beamforming and beyond

Principal investigatorNSERC2022Alliance Grants

Principal investigators: Rivaz, Hassan H

$25,000

Towards Early and Accessible Diagnosis of Breast Cancer Related Lymphedema And Its Social Implications

Principal investigatorSSHRC2022New Frontiers in Research Fund - Exploration

Principal investigators: Rivaz, Hassan

Keywords: lymphedema machine leaning ultrasound POCUS deep learning elastography radio-frequency (RF) data

$125,000

Towards Early and Accessible Diagnosis of Breast Cancer Related Lymphedema And Its Social Implications

Principal investigatorSSHRC2022New Frontiers in Research Fund - Exploration

Principal investigators: Rivaz, Hassan

Keywords: lymphedema; machine leaning; ultrasound; POCUS; deep learning; elastography; radio-frequency (RF) data

$125,000

Development of novel machine learning algorithms for registration of point clouds and tracking surgical tools

Principal investigatorNSERC2021Alliance Grants

Principal investigators: Rivaz, Hassan

$163,002

Development of machine learning techniques for accessible and inexpensive imaging of COVID-19 with ultrasound

Principal investigatorNSERC2020Alliance Grants

Principal investigators: Rivaz, Hassan

$50,000

Making Sense of the Data Trove Hidden in Medical Ultrasound Signals

Principal investigatorNSERC2020Discovery Grants Program - Individual

Principal investigators: Rivaz, Hassan

$165,000

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

Electrical and Computer Engineering
Physics
Institut de génie biomédical
Cardiology & Clinical Epidemiology
Medicine
Electrical Engineering
Psychology
Other

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

Julien Cohen-Adad

Electrical Engineering

1 shared papers, latest 2025

Pedro Rosa-Neto

Neurology and Neurosurgery

1 shared papers, latest 2023

Jean-Paul Soucy

Institut de génie biomédical

1 shared papers, latest 2023

Jonathan Afilalo

Cardiology & Clinical Epidemiology

1 shared papers, latest 2025

Louis-Nicolas Veilleux

Faculty

1 shared papers, latest 2024

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 2026

Subject: Prospective PhD student: Breast Cancer Dear Professor Rivaz, 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-based femoral reconstruction from intraoperative point clouds for enhanced knee arthroplasty registration." (2026), 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 "Accessible Diagnosis and Staging of Breast Cancer-Related Lymphedema with AI-Powered Point of Care Ultrasound" (2026), 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]

Hassan Rivaz

Research

Latest papers

Latest funding

Deep learning-based femoral reconstruction from intraoperative point clouds for enhanced knee arthroplasty registration.

Statistical shape model-based estimation of registration error in computer-assisted total knee arthroplasty.

Characterizing forearm skeletal muscle composition and function in breast cancer-related lymphedema using B-mode ultrasonography.

MedCLIP-SAMv2: Towards universal text-driven medical image segmentation.

Deformable detection transformers for domain adaptable ultrasound localization microscopy with robustness to point spread function variations.

Joint enhancement of automatic chest x-ray diagnosis and radiological gaze prediction with multistage cooperative learning.

Ultrasound and MRI-based evaluation of relationships between morphological and mechanical properties of the lower lumbar multifidus muscle in chronic low back pain.

CASCADE-FSL: Few-shot learning for collateral evaluation in ischemic stroke.

Leveraging deep learning for nonlinear shape representation in anatomically parameterized statistical shape models.

Ultrasound Segmentation Using Semi-Supervised Learning: Application in Point-of-Care Sarcopenia Assessment.

Accessible Diagnosis and Staging of Breast Cancer-Related Lymphedema with AI-Powered Point of Care Ultrasound

Accessible Diagnosis and Staging of Breast Cancer-Related Lymphedema with AI-Powered Point of Care Ultrasound

Improved Total Knee Arthroplasty Registration Using Deep Learning and Ultrasound

Quantitative ultrasound to improve detection and diagnosis of liver cancer

Unsupervised deep learning for ultrasound beamforming and beyond

Towards Early and Accessible Diagnosis of Breast Cancer Related Lymphedema And Its Social Implications

Towards Early and Accessible Diagnosis of Breast Cancer Related Lymphedema And Its Social Implications

Development of novel machine learning algorithms for registration of point clouds and tracking surgical tools

Development of machine learning techniques for accessible and inexpensive imaging of COVID-19 with ultrasound

Making Sense of the Data Trove Hidden in Medical Ultrasound Signals

Frequent collaborators

Maryse Fortin

Sandrine De Ribaupierre

Julien Cohen-Adad

Mathieu Roy

Pedro Rosa-Neto

Mathieu Roy

Jean-Paul Soucy

Brandon Helfield

Jonathan Afilalo

Jonathan Afilalo

Louis-Nicolas Veilleux