Dafna Sussman, Toronto Metropolitan University

Research

Automatic Image Processing Clinical Validation Diagnostic Imaging Fetal Mri Image Classification Image Segmentation Machine Learning Radiology

Latest papers

An end-to-end pipeline for automated fetal brain segmentation and biometry from 3D SSFP MRI.
Frontiers in neuroscience · 2026 · senior author
Fetal Assessment Suite (FetAS): a web-based platform for automatic fetal MRI analysis using AI.
Scientific reports · 2025 · senior author
Prediction of preterm birth from cervical length measurements in twin pregnancies using machine learning.
Scientific reports · 2025 · senior author

All 32 publications

Latest funding

FetAS: Fetal Assessment Suite to Facilitate Rapid Fetal MRI Diagnosis using Artificial Intelligence
CIHR · 2023 · Nominated PI
$906,526
Anthropomorphic motion phantom of the human fetus
NSERC · 2022 · Principal investigator
$20,000
Automatic COVID-19 pregnant patient prognosis algorithm_x000d_
NSERC · 2020 · Principal investigator
$50,000

All 6 grants and awards

32 publications.

01

An end-to-end pipeline for automated fetal brain segmentation and biometry from 3D SSFP MRI.

Modarai Y, Lim A, Lo J, Wagner MW, Miller E, Vidarsson L, Ertl-Wagner B, Sussman D

Frontiers in neuroscience2026Senior author

DOI: 10.3389/fnins.2026.1870124 PMID: 42495270

02

Fetal Assessment Suite (FetAS): a web-based platform for automatic fetal MRI analysis using AI.

Costanzo A, Lim A, Pereira M, Modarai Y, Lo J, Momeni N, Eisenstat J, Wagner MW, Vidarsson L, Miller E, Ertl-Wagner B, Sussman D

Scientific reports2025Senior author

DOI: 10.1038/s41598-025-32298-y PMID: 41402396

03

Prediction of preterm birth from cervical length measurements in twin pregnancies using machine learning.

Costanzo A, Szymanowski M, Melamed N, Sussman D

Scientific reports2025Senior author

DOI: 10.1038/s41598-025-19803-z PMID: 41087513

04

Ultrasound Radiomics Correlating With Clinical Markers for Enhanced Detection of Placenta Accreta Spectrum.

Young D, Khan N, Hobson SR, Sussman D

Ultrasound in medicine & biology2025Senior author

DOI: 10.1016/j.ultrasmedbio.2025.06.018 PMID: 40670260

05

Design and testing of an MRI-conditional six-degree-of-freedom phantom robot.

Dunn A, Lee M, Sadanand S, Khoobani M, Hassan T, Tavallaei MA, Sussman D

Physics in medicine and biology2025Senior author

DOI: 10.1088/1361-6560/ae0973 PMID: 40972656

06

Magnetization transfer MRI of third trimester fetal brain: a pilot of gestational myelin imaging.

Sadanand S, Stobbe R, van Mieghem T, Shinar S, Krishnan P, Miller E, Stanisz G, Sussman D

Frontiers in pediatrics2025Senior author

DOI: 10.3389/fped.2025.1443387 PMID: 40416434

07

Scoping review of magnetic resonance motion imaging phantoms.

Dunn A, Wagner S, Sussman D

Magma (New York, N.Y.)2024Senior author

DOI: 10.1007/s10334-024-01164-9 PMID: 38739218

08

Diagnosis of placenta accreta spectrum using ultrasound texture feature fusion and machine learning.

Young D, Khan N, Hobson SR, Sussman D

Computers in biology and medicine2024Senior author

DOI: 10.1016/j.compbiomed.2024.108757 PMID: 38878399

09

Predicting adverse outcomes in pregnant patients positive for SARS-CoV-2: a machine learning approach- a retrospective cohort study

Young D, Houshmand B, Tan CC, Kirubarajan A, Parbhakar A, Dada J, Whittle W, Sobel ML, Gomez LM, Rüdiger M

BMC Pregnancy and Childbirth202314 citationsSenior authorOpen Access

DOI: 10.1186/s12884-023-05679-2 PMID: W4385495211

10

Effect of Injection Parameters on the MRI and Dielectric Properties of Condensation-Cured Silicone.

Cristant C, Kolasangiani K, Sadanand S, Bougherara H, Sussman D

Polymers2023Senior author

DOI: 10.3390/polym15244670 PMID: 38139922

FetAS: Fetal Assessment Suite to Facilitate Rapid Fetal MRI Diagnosis using Artificial Intelligence

Nominated PICIHR2023Project Grant

Principal investigators: Sussman, Dafna; Ertl-Wagner, Birgit B

Keywords: Automatic Image Processing; Clinical Validation; Diagnostic Imaging; Fetal Mri; Image Classification; Image Segmentation; Machine Learning; Radiology; Time Efficiency

$906,526

Anthropomorphic motion phantom of the human fetus

Principal investigatorNSERC2022Idea to Innovation

Principal investigators: Sussman, Dafna D

$20,000

Automatic COVID-19 pregnant patient prognosis algorithm_x000d_

Principal investigatorNSERC2020Alliance Grants

Principal investigators: Sussman, Dafna

$50,000

Magnetic Resonance Tools for Fetal Developmental and Metabolic Assessment

Principal investigatorNSERC2018Discovery Launch Supplement

Principal investigators: Sussman, Dafna

$12,500

In-vivo glucoCEST MRI - The future of organ metabolic imaging

Principal investigatorNSERC2018Engage Grants Program

Principal investigators: Sussman, Dafna

$25,000

Magnetic Resonance Tools for Fetal Developmental and Metabolic Assessment

Principal investigatorNSERC2018Discovery Grants Program - Individual

Principal investigators: Sussman, Dafna

$168,000

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

Biomedical Engineering
Neurosciences and Mental Health
Radiation Oncology
Obstetrics and Gynecology
Medicine
Obstetrics & Gynecology
Pediatrics
Other

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

Birgit Ertl-Wagner

Biomedical Engineering

7 shared papers, latest 2026

Birgit Ertl-Wagner

Neurosciences and Mental Health

7 shared papers, latest 2026

Greg Wells

Biomedical Engineering

4 shared papers, latest 2019

Rohan D'Souza

Obstetrics & Gynecology

1 shared papers, latest 2023

Nir Melamed

Obstetrics and Gynecology

1 shared papers, latest 2025

Greg Stanisz

Radiation Oncology

1 shared papers, latest 2025

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 2023

Subject: Prospective PhD student: Automatic Image Processing Dear Professor Sussman, 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 "An end-to-end pipeline for automated fetal brain segmentation and biometry from 3D SSFP MRI." (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 "FetAS: Fetal Assessment Suite to Facilitate Rapid Fetal MRI Diagnosis using Artificial Intelligence" (2023), 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]

Dafna Sussman

Research

Latest papers

Latest funding

An end-to-end pipeline for automated fetal brain segmentation and biometry from 3D SSFP MRI.

Fetal Assessment Suite (FetAS): a web-based platform for automatic fetal MRI analysis using AI.

Prediction of preterm birth from cervical length measurements in twin pregnancies using machine learning.

Ultrasound Radiomics Correlating With Clinical Markers for Enhanced Detection of Placenta Accreta Spectrum.

Design and testing of an MRI-conditional six-degree-of-freedom phantom robot.

Magnetization transfer MRI of third trimester fetal brain: a pilot of gestational myelin imaging.

Scoping review of magnetic resonance motion imaging phantoms.

Diagnosis of placenta accreta spectrum using ultrasound texture feature fusion and machine learning.

Predicting adverse outcomes in pregnant patients positive for SARS-CoV-2: a machine learning approach- a retrospective cohort study

Effect of Injection Parameters on the MRI and Dielectric Properties of Condensation-Cured Silicone.

FetAS: Fetal Assessment Suite to Facilitate Rapid Fetal MRI Diagnosis using Artificial Intelligence

Anthropomorphic motion phantom of the human fetus

Automatic COVID-19 pregnant patient prognosis algorithm_x000d_

Magnetic Resonance Tools for Fetal Developmental and Metabolic Assessment

In-vivo glucoCEST MRI - The future of organ metabolic imaging

Magnetic Resonance Tools for Fetal Developmental and Metabolic Assessment

Frequent collaborators

Birgit Ertl-Wagner

Birgit Ertl-Wagner

Greg Wells

Jurgen Germann

Rohan D'Souza

Nir Melamed

Rohan D'Souza

Steven Miller

Greg Stanisz