Julien Cohen-Adad

Paul Hoareau

Maîtrise recherche - Polytechnique

paul.hoareau@mila.quebec

youssef.laatar@mila.quebec

Youssef Laatar

Maîtrise recherche - Polytechnique

nathan.molinier@mila.quebec

Nathan Molinier

Doctorat - Polytechnique

Publications

Body size and intracranial volume interact with the structure of the central nervous system: A multi-center in vivo neuroimaging study

René Labounek

Monica T. Bondy

Amy Paulson

Sandrine Bédard

Mihael Abramovic

Eva Alonso‐Ortiz

Nicole Atcheson

Laura Barlow

Robert Barry

Markus Barth

Marco Battiston

Christian Büchel

Matthew D. Budde

Virginie Callot

Anna Combes

Benjamin De Leener

Maxime Descoteaux

Paulo Loureiro de Sousa

Marek Dostál

Julien Doyon … (voir 73 de plus)

Adam Dvorak

Falk Eippert

Karla R. Epperson

Kevin Epperson

Patrick Freund

Jürgen Finsterbusch

Alexandru Foias

Michela Fratini

Issei Fukunaga

Claudia A. M. Gandini Wheeler‐Kingshott

Giancarlo Germani

Guillaume Gilbert

Federico Giove

Francesco Grussu

Akifumi Hagiwara

Pierre‐Gilles Henry

Tomáš Horák

Masaaki Hori

James M. Joers

Kouhei Kamiya

Haleh Karbasforoushan

Miloš Keřkovský

Ali Khatibi

Joo-Won Kim

Nawal Kinany

Hagen H. Kitzler

Shannon Kolind

Yazhuo Kong

Petr Kudlička

Paul Kuntke

Nyoman D. Kurniawan

Sławomir Kuśmia

Maria Marcella Laganà

Cornelia Laule

Christine Law

Tobias Leutritz

Yaou Liu

Sara Llufriú

Sean Mackey

Allan R. Martin

Eloy Martínez‐Heras

Loan Mattera

Kristin P. O’Grady

Nico Papinutto

Daniel S. Papp

Deborah Pareto

Todd B. Parrish

Anna Pichiecchio

Ferrán Prados

Àlex Rovira

Marc J. Ruitenberg

Rebecca S. Samson

Giovanni Savini

Maryam Seif

Alan C. Seifert

Alex K. Smith

Seth A. Smith

Zachary A. Smith

Elisabeth Solana

Yuichi Suzuki

George Tackley

Alexandra Tinnermann

Dimitri Van De Ville

Marios Yiannakas

Kenneth A. Weber

Nikolaus Weiskopf

Richard G. Wise

Patrik O. Wyss

Junqian Xu

Julien Cohen‐Adad

Christophe Lenglet

Igor Nestrašil

Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controllin… (voir plus)g for sources of biological variation such as subject’s sex and age. However, corrections for body size (i.e., height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1 ± 6.6 years old, 125 females). We show that body height correlates with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44 ≤ r ≤ 0.62). Intracranial volume (ICV) correlates with body height (r = 0.46) and the brain volumes and CSA-WM (0.37 ≤ r ≤ 0.77). In comparison, age correlates with cortical GM volume, precentral GM volume, and cortical thickness (-0.21 ≥ r ≥ -0.27). Body weight correlates with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20 ≥ r ≥ -0.23). Body weight further correlates with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r = -0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlates with brain volumes (0.39 ≤ r ≤ 0.64), and with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22 ≥ r ≥ -0.25). Linear mixture of age, sex, or sex and age, explained 2 ± 2%, 24 ± 10%, or 26 ± 10%, of data variance in brain volumetry and SC CSA. The amount of explained variance increased to 33 ± 11%, 41 ± 17%, or 46 ± 17%, when body height, ICV, or body height and ICV were added into the mixture model. In females, the explained variances halved suggesting another unidentified biological factor(s) determining females’ central nervous system (CNS) morphology. In conclusion, body size and ICV are significant biological variables. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure; and body size and ICV should be considered as covariates in statistical analyses. Normalization of different brain regions with ICV diminishes their correlations with body size, but simultaneously amplifies ICV-related variance (r = 0.72 ± 0.07) and suppresses volume variance of the different brain regions (r = 0.12 ± 0.19) in the normalized measurements.

2024-12-31

Imaging Neuroscience (publié)

EPISeg: Automated segmentation of the spinal cord on echo planar images using open-access multi-center data

Rohan Banerjee

Merve Kaptan

Alexandra Tinnermann

Ali Khatibi

Alice Dabbagh

Christian Büchel

Christian W. Kündig

Christine Law

Dario Pfyffer

David J. Lythgoe

Dimitra Tsivaka

Dimitri Van De Ville

Falk Eippert

Fauziyya Muhammad

Gary H. Glover

Gergely David

Grace Haynes

Jan Haaker

J.C. Brooks

Jürgen Finsterbusch … (voir 21 de plus)

Katherine T. Martucci

Kimberly J. Hemmerling

Mahdi Mobarak-Abadi

Mark A. Hoggarth

Matthew A. Howard

Molly G. Bright

Nawal Kinany

Olivia S. Kowalczyk

Patrick Freund

Robert Barry

Sean Mackey

Shahabeddin Vahdat

Simon Schading‐Sassenhausen

Stephen B. McMahon

Todd Parish

Véronique Marchand‐Pauvert

Yufen Chen

Zachary A. Smith

Kenneth A. Weber

Benjamin De Leener

Julien Cohen‐Adad

Functional magnetic resonance imaging (fMRI) of the spinal cord is relevant for studying sensation, movement, and autonomic function. Prepro… (voir plus)cessing of spinal cord fMRI data involves segmentation of the spinal cord on gradient-echo echo planar imaging (EPI) images. Current automated segmentation methods do not work well on these data, due to the low spatial resolution, susceptibility artifacts causing distortions and signal drop-out, ghosting, and motion-related artifacts. Consequently, this segmentation task demands a considerable amount of manual effort which takes time and is prone to user bias. In this work, we (i) gathered a multi-center dataset of spinal cord gradient-echo EPI with ground-truth segmentations and shared it on OpenNeuro https://openneuro.org/datasets/ds005143/versions/1.3.1 and (ii) developed a deep learning-based model, EPISeg, for the automatic segmentation of the spinal cord on gradient-echo EPI data. We observe a significant improvement in terms of segmentation quality compared with other available spinal cord segmentation models. Our model is resilient to different acquisition protocols as well as commonly observed artifacts in fMRI data. The training code is available at https://github.com/sct-pipeline/fmri-segmentation/, and the model has been integrated into the Spinal Cord Toolbox as a command-line tool.

2024-12-31

Imaging Neuroscience (publié)

Morphometric characteristics of tibial nerve and their relationship with age

Shahram Oveisgharan

Armand Collin

Jingyun Yang

Sue E. Leurgans

Veronique VanderHorst

David A. Bennett

Osvaldo Delbono

Aron S. Buchman

Peripheral nerve comprises a crucial component of the distributed motor/sensory system. However, there is a paucity of data on peripheral ne… (voir plus)rve morphology derived from large numbers of older adults. This study aimed to quantify the morphometric characteristics of myelinated nerve fibres of the tibial nerve obtained from deceased community-dwelling older adults and examine their association with age. The tibial nerves were obtained from consecutive autopsies of older adults without a history of diabetes who were participants of the Rush Memory and Aging Project, an ongoing longitudinal clinical-autopsy study. A nerve fascicle, obtained from a fixed popliteal segment of the tibial nerve, was separated from the blood vessels and adipose tissue for postmortem examination under an optical microscope. Morphometric characteristics of the myelinated nerve fibres were automatically segmented and quantified using our open-source software AxonDeepSeg. The participants (N = 140) had a mean age of 92.0 years (SD = 5.4) at death, and 72.1% (N = 101) were women. We examined 754 247 myelinated nerve fibres, with an average 5387 (SD = 3436) nerve fibres per participant. The average diameter of myelinated nerve fibres was 4.9 µm (SD = 3.1), axon diameter was 2.0 µm (SD = 1.4), myelin thickness was 1.4 µm (SD = 0.96) and the g-ratio (ratio of axon diameter to myelinated nerve fibre diameter) was 0.45 (SD = 0.17). The relationship between axon diameter and myelin thickness was nonlinear. Myelin was thicker in larger axons up to a diameter of 8 µm, beyond which myelin thickness plateaued. Older age at death was associated with smaller myelinated nerve fibres, smaller axons and thinner myelin. However, age at death was not correlated with myelinated nerve fibre density and was not associated with the average of g-ratio. The association between older age and smaller myelinated nerve fibres was largely attributable to a lower percentage of myelinated nerve fibres >8 µm. We conclude that the smaller tibial myelinated nerve fibres observed in older adults may reflect axonal atrophy rather than degeneration and regeneration of the myelinated nerve fibres. Further research is needed to investigate the pathologies and molecular mechanisms underlying these age-related morphometric changes and their clinical implications in older adults.

2024-12-31

Brain Communications (publié)

Rootlets-based registration to the PAM50 spinal cord template

Sandrine Bédard

Valeria Oliva

Kenneth A. Weber II

Spinal cord functional MRI studies require precise localization of spinal levels for reliable voxelwise group analyses. Traditional template… (voir plus)-based registration of the spinal cord uses intervertebral discs for alignment. However, substantial anatomical variability across individuals exists between vertebral and spinal levels. This study proposes a novel registration approach that leverages spinal nerve rootlets to improve alignment accuracy and reproducibility across individuals. We developed a registration method leveraging dorsal cervical rootlets segmentation and aligning them non-linearly with the PAM50 spinal cord template. Validation was performed on a multi-subject, multi-site dataset (n=267, 44 sites) and a multi-subject dataset with various neck positions (n=10, 3 sessions). We further validated the method on task-based functional MRI (n=23) to compare group-level activation maps using rootlet-based registration to traditional disc-based methods. Rootlet-based registration showed superior alignment across individuals compared to the traditional disc-based method. Notably, rootlet positions were more stable across neck positions. Group-level analysis of task-based functional MRI using rootlet-based increased Z scores and activation cluster size compared to disc-based registration (number of active voxels from 3292 to 7978). Rootlet-based registration enhances both inter- and intra-subject anatomical alignment and yields better spatial normalization for group-level fMRI analyses. Our findings highlight the potential of rootlet-based registration to improve the precision and reliability of spinal cord neuroimaging group analysis.

2024-12-31

Imaging Neuroscience (publié)

arxiv.org

Spinal cord demyelination predicts neurological deterioration in patients with mild degenerative cervical myelopathy

Abdul Al-Shawwa

Michael Craig

Kalum Ost

David Anderson

Steve Casha

W Bradley Jacobs

Nathan Evaniew

Saswati Tripathy

Jacques Bouchard

Peter Lewkonia

Fred Nicholls

Alex Soroceanu

Ganesh Swamy

Kenneth C Thomas

Stephan duPlessis

Michael MH Yang

Nicholas Dea

Jefferson R Wilson

David W Cadotte

Degenerative cervical myelopathy (DCM) is the most common form of atraumatic spinal cord injury globally. Clinical guidelines regarding surg… (voir plus)ery for patients with mild DCM and minimal symptoms remain uncertain. This study aims to identify imaging and clinical predictors of neurological deterioration in mild DCM and explore pathophysiological correlates to guide clinical decision-making. Patients with mild DCM underwent advanced MRI scans that included T2-weighted, diffusion tensor imaging and magnetisation transfer (MT) sequences, along with clinical outcome measures at baseline and 6-month intervals after enrolment. Quantitative MRI (qMRI) metrics were derived above and below maximally compressed cervical levels (MCCLs). Various machine learning (ML) models were trained to predict 6 month neurological deterioration, followed by global and local model interpretation to assess feature importance. A total of 49 patients were followed for a maximum of 2 years, contributing 110 6-month data entries. Neurological deterioration occurred in 38% of cases. The best-performing ML model, combining clinical and qMRI metrics, achieved a balanced accuracy of 83%, and an area under curve-receiver operating characteristic of 0.87. Key predictors included MT ratio (demyelination) above the MCCL in the dorsal and ventral funiculi and moderate tingling in the arm, shoulder or hand. qMRI metrics significantly improved predictive performance compared to models using only clinical (bal. acc=68.1%) or imaging data (bal. acc=57.4%). Reduced myelin content in the dorsal and ventral funiculi above the site of compression, combined with sensory deficits in the hands and gait/balance disturbances, predicts 6-month neurological deterioration in mild DCM and may warrant early surgical intervention.

2024-12-31

BMJ Neurology Open (publié)

Towards contrast-agnostic soft segmentation of the spinal cord

Sandrine Bédard

Enamundram Naga Karthik

Charidimos Tsagkas

Emanuele Pravatà

Cristina Granziera

Andrew Smith

Kenneth Arnold Weber II

Spinal cord segmentation is clinically relevant and is notably used to compute spinal cord cross-sectional area (CSA) for the diagnosis and … (voir plus)monitoring of cord compression or neurodegenerative diseases such as multiple sclerosis. While several semi and automatic methods exist, one key limitation remains: the segmentation depends on the MRI contrast, resulting in different CSA across contrasts. This is partly due to the varying appearance of the boundary between the spinal cord and the cerebrospinal fluid that depends on the sequence and acquisition parameters. This contrast-sensitive CSA adds variability in multi-center studies where protocols can vary, reducing the sensitivity to detect subtle atrophies. Moreover, existing methods enhance the CSA variability by training one model per contrast, while also producing binary masks that do not account for partial volume effects. In this work, we present a deep learning-based method that produces soft segmentations of the spinal cord. Using the Spine Generic Public Database of healthy participants (

2024-12-31

Medical Image Anal. (publié)

arxiv.org

TransCeption: Enhancing medical image segmentation with an inception-like transformer design for efficient feature fusion

Reza Azad

Yiwei Jia

Ehsan Khodapanah Aghdam

Dorit Merhof

2024-12-31

Comput. Vis. Media (publié)

Longitudinal reproducibility of brain and spinal cord quantitative MRI biomarkers

Mathieu Boudreau

Agah Karakuzu

Arnaud Boré

Basile Pinsard

Kiril Zelenkovski

Eva Alonso-Ortiz

Julie Boyle

Lune Bellec

Quantitative MRI (qMRI) promises better specificity, accuracy, repeatability, and reproducibility relative to its clinically-used qualitativ… (voir plus)e MRI counterpart. Longitudinal reproducibility is particularly important in qMRI. The goal is to reliably quantify tissue properties that may be assessed in longitudinal clinical studies throughout disease progression or during treatment. In this work, we present the initial data release of the quantitative MRI portion of the Courtois project on neural modelling (CNeuroMod), where the brain and cervical spinal cord of six participants were scanned at regular intervals over the course of several years. This first release includes 3 years of data collection and up to 10 sessions per participant using quantitative MRI imaging protocols (T1, magnetization transfer (MTR, MTsat), and diffusion). In the brain, T1MP2RAGE, fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD) all exhibited high longitudinal reproducibility (intraclass correlation coefficient – ICC ≃ 1 and within-subject coefficient of variations – wCV 1%). The spinal cord cross-sectional area (CSA) computed using T2w images and T1MTsatexhibited the best longitudinal reproducibility (ICC ≃ 1 and 0.7 respectively, and wCV 2.4% and 6.9%). Results from this work show the level of longitudinal reproducibility that can be expected from qMRI protocols in the brain and spinal cord in the absence of hardware and software upgrades, and could help in the design of future longitudinal clinical studies.

2024-12-09

Imaging Neuroscience (publié)

Automatic Segmentation of the Spinal Cord Nerve Rootlets

Theo Mathieu

Raphaëlle Schlienger

Olivia S. Kowalczyk

Precise identification of spinal nerve rootlets is relevant to delineate spinal levels for the study of functional activity in the spinal co… (voir plus)rd. The goal of this study was to develop an automatic method for the semantic segmentation of spinal nerve rootlets from T2-weighted magnetic resonance imaging (MRI) scans. Images from two open-access MRI datasets were used to train a 3D multi-class convolutional neural network using an active learning approach to segment C2-C8 dorsal nerve rootlets. Each output class corresponds to a spinal level. The method was tested on 3T T2-weighted images from datasets unseen during training to assess inter-site, inter-session, and inter-resolution variability. The test Dice score was 0.67 +- 0.16 (mean +- standard deviation across testing images and rootlets levels), suggesting a good performance. The method also demonstrated low inter-vendor and inter-site variability (coefficient of variation <= 1.41 %), as well as low inter-session variability (coefficient of variation <= 1.30 %) indicating stable predictions across different MRI vendors, sites, and sessions. The proposed methodology is open-source and readily available in the Spinal Cord Toolbox (SCT) v6.2 and higher.

2024-11-25

International Society for Magnetic Resonance in Medicine Scientific Meeting and Exhibition (inconnu)

arxiv.org

Canadian Spine Society

Antoine Dionne

Firoz Miyanji

Jennifer A. Dermott

Sarah Hardy

Dorothy Kim

Samuel Yoon

Firoz Miyanji

Marjolaine Roy‐Beaudry

Jessica Romeo

Vivien Chan

Brett Rocos

Peter Tretiakov

Stephen Lewis

Vishal Varshney

Rémi Pelletier-Roy

Ariel Zohar

Aazad Abbas

Raja Rampersaud

Maroun Rizkallah

Nikolaus Koegl … (voir 970 de plus)

Brandon J. Herrington

Ramtin Hakimjavadi

Raja Rampersaud

Alexandre Chenevert

Brent Rosenstein

Zhi Wang

Aditya Raj

Abdullah Alduwaisan

Jeffrey Hebert

Nikolaus Koegl

Michael Craig

Armaan K. Malhotra

Nathan Evaniew

Eva Y. Liu

Husain Shakil

Philippe Phan

Thamer Alfawaz

Julien Francisco Zaldivar-Jolissaint

Michael G. Fehlings

Jessica C. W. Wang

Rohail Mumtaz

Ragavan Manoharan

Jenna Smith‐Forrester

Eva Y. Liu

Maria S. Rachevits

Alysa Almojuela

Mark Abdelnour

Taylor A. Smith

Steven Qiu

Ahmad Essa

Husain Shakil

Ryan Sandarage

Naama Rotem-Kohavi

Brian K. Kwon

Rachael H. Jaffe

Newton Cho

Sean D. Christie

Marcel F. Dvorak

Antoine Dionne

Lukas Grassner

Mark A. MacLean

Émile Brouillard

Julien Francisco Zaldivar-Jolissaint

Aysha Allard Brown

Jeff D. Golan

Drew A. Bednar

Prarthan Amin

Amanda Vandewint

Raja Rampersaud

Manmeet Dhiman

Connor P. O’Brien

Luke LaRochelle

Dorothy Kim

Jennifer A. Dermott

Chanelle Montpetit

Emma Nadler

Daniel Wolfe

Husain Shakil

Marco Pérez Caceres

William Chu Kwan

Van Tri Truong

Maroun Rizkallah

Zhi Wang

Yan Gabriel Morais David Silva

Ahmad Essa

Michael Craig

Antoine Dionne

William Chu Kwan

Jérémie Thibault

Maxime Bouthillier

Luke Reda

Colton Kennedy

Maryam Rezaeezadeh Roukerd

Philippe Phan

Khushdeep S. Vig

Shaurya Gupta

W. Bradley Jacobs

Christopher D. Witiw

Dorothy J. Kim

Rachael Jaffe

Prarthan C. Amin

Jin Tong Du

Siril Teja Dukkipati

Elizabeth Byers

Shannon Rockall

Aaron A. Varga

Lutz M. Weise

Isaac Turkstra

Sarah Hardy

Yan Gabriel Morais David Silva

Ryan Greene

Alwalaa Althagafi

Christopher Witiw

W. Bradley Jacobs

Timothy Lasswell

Abdulrahman Hamdoon

Kirsten A. Schuler

Kalum J. Ost

Mohamed Sarraj

Hani Nouran Alharbi

Julien Francisco Zaldivar-Jolissaint

Sara Gustafson

Drew Alexander Bednar

Brett Rocos

Ravi Ghag

Amit Parekh

Kevin Smit

Sofía Frank

Jérémie Thibault

Antoine Dionne

Manjot S. Birk

Stephen Lewis

Elen Mullaj

Ariel Zohar

Taylor J. Bader

Stephen Joel Lewis

Peyton Lloyd Lawrence

Jordan J. Levett

Phillip de Muelenaere

Olivia C. Iorio

Felicia Manocchio

Hamza Mahdi

Steven Qiu

Majeed Al-Zakri

Hubert Labelle

Julie Joncas

Stefan Parent

Jean-Marc Mac-Thiong

Baron Lonner

Ali Eren

Patrick Cahill

Stefan Parent

Peter Newton

Liisa Jaakkimainen

Teresa To

Maryse Bouchard

Andrew Howard

David E. Lebel

Armaan K. Malhotra

Jennifer Dermott

Dilani Thevarajah

Karen D.A. Mathias

Samuel Yoon

Rajendra Sakhrekar

David E. Lebel

Ayesha Hadi

Andrea Doria

Aya Mitani

Jennifer Dermott

Andrew Howard

David Lebel

Karen Mathias

Jennifer Dermott

David Lebel

Peter Newton

Baron Lonner

Tracey Bastrom

Amer Samdani

Marie Beausejour

Rachelle Imbeault

Justin Dufresne

Stefan Parent

Holly Livock

Kevin Smit

James Jarvis

Andrew Tice

Robert Cho

Selina Poon

David L. Skaggs

Geoffrey K. Shumilak

Juan P. Sardi

Anastasios Charalampidis

Jeff Gum

Stephen J. Lewis

Oluwatobi Onafowokan

Jamshaid Mir

Ankita Das

Tyler Williamson

Pooja Dave

Bailey Imbo

Jordan Lebovic

Pawel Jankowski

Peter G. Passias

Yousef Aljamaan

Lawrence G. Lenke

Justin Smith

Ramesh Sahjpaul

Scott Paquette

Jill Osborn

Michael Asmussen

Manjot Birk

Taryn Ludwig

Fred Nicholls

Janneke Loomans

Ferran Pellise

Justin S. Smith

So Kato

Zeeshan Sardar

Lawrence Lenke

Stephen J. Lewis

Jay Toor

Gurjovan Sahi

Dusan Kovacevic

Johnathan Lex

Firoz Miyanji

Anthony V. Perruccio

Nizar Mahomed

Mayilee Canizares

Michel Alexandre Lebreton

Ghassan Boubez

Jesse Shen

Fidaa Alshakfa

Yousef Kamel

Galil Osman

Zhi Wang

Renan R. Fernandes

Jennifer C. Urquhart

Yoga R. Rampersaud

Chris S. Bailey

Tinghua Zhang

Zachary DeVries

Eugene K. Wai

Stephen P. Kingwell

Alexandra Stratton

Eve Tsai

Zhi Wang

Philippe Phan

Noah Fine

Laura Stone

Mohit Kapoor

Sonia Bédard

Greg McIntosh

Julien Goulet

Jerome Couture

CSORN Investigators

Bernard LaRue

Meaghan Rye

Alexa Roussac

Neda Naghdi

Luciana G. Macedo

James Elliott

Richard DeMont

Michael H. Weber

Véronique Pepin

Geoffrey Dover

Maryse Fortin

Maroun Rizkallah

Jesse Shen

Michel Alexandre Lebreton

Edisond Florial

Fidaa Alshakfa

Ghassan Boubez

Greg McIntosh

Yoga Raja Rampersaud

Ramtin Hakimjavadi

Tinghua Zhang

Kim Phan

Alexandra Stratton

Eve Tsai

Stephen Kingwell

Eugene Wai

Philippe Phan

Sarah Nowell

Niels Wedderkopp

Amanda Vandewint

Neil Manson

Edward Abraham

Christopher Small

Najmedden Attabib

Erin Bigney

Abdul Al-Shawwa

Kalum Ost

Saswati Tripathy

Nathan Evaniew

Bradley Jacobs

David Cadotte

Nathan Evaniew

Nicolas Dea

CSORN Investigators

Greg McIntosh

Jefferson R. Wilson

Christopher S. Bailey

Y. Raja Rampersaud

W. Bradley Jacobs

Philippe Phan Phan

Andrew Nataraj

David W. Cadotte

Michael H. Weber

Kenneth C. Thomas

Neil Manson

Najmedden Attabib

Jérôme Paquet

Sean D. Christie

Jefferson R. Wilson

Hamilton Hall

Charles G. Fisher

Greg McIntosh

Nicolas Dea

Amit R.L. Persad

Nathan Baron

Daryl Fourney

CSORN Investigators

Nathan Evaniew

Jefferson R. Wilson

Nicolas Dea

Jingyi Huang

Nader Fallah

Charlotte Dandurand

Tinghua Zhang

Alexandra Stratton

Eve Tsai

Eugene Wai

Stephen Kingwell

Zhi Wang

Philippe Phan

CSORN Investigators

Raphaële Charest-Morin

Greg McIntosh

Karlo M. Pedro

Mohammed Ali Alvi

Raphaële Charest-Morin

Nicolas Dea

Charles Fisher

Marcel Dvorak

Brian Kwon

Tamir Ailon

Scott Paquette

John Street

Charlotte Dandurand

Khaled Skaik

Eugene K. Wai

Stephen Kingwell

Alexandra Stratton

Eve Tsai

Philippe Tran Nhut Phan

Zhi Wang

CSORN Investigators

Greg McIntosh

Yoga R. Rampersaud

JoAnne E. Douglas

Evan Nemeth

Jacob Alant

Sean Barry

Andrew Glennie

William Oxner

Lutz Weise

Sean Christie

Amit R.L. Persad

Sabahat Saeed

Patrick Toyota

Jack Su

Braeden Newton

Nicole Coote

Daryl Fourney

Helen Razmjou

Susan Robarts

Albert Yee

Joel Finkelstein

Frederick Zeiler

Sarvesh Logsetty

Perry Dhaliwal

Yuxin Zhang

Eugene Wai

Stephen P. Kingwell

Alexandra Stratton

Eve Tsai

Philippe T. Phan

CSORN Investigators

Christopher Small

Erin Bigney

Eden Richardson

Jillian Kearney

Neil Manson

Edward Abraham

Najmedden Attabib

Michael Bond

Stephan Dombrowski

Gwyneth Price

Jose Manuel García-Moreno

Jeffrey Hebert

Vithushan Surendran

Victoria Shi Emily Cheung

Sophie Ngana

Muhammad A. Qureshi

Sunjay V. Sharma

Markian Pahuta

Daipayan Guha

Husain Shakil

Armaan Malhotra

James Byrne

Jetan Badhiwala

Eva Yuan

Yingshi He

Andrew Jack

Francois Mathieu

Jefferson R. Wilson

Christopher D. Witiw

Armaan K. Malhotra

Eva Yuan

Christopher W. Smith

Erin M. Harrington

Alick P. Wang

Karim Ladha

Avery B. Nathens

Jefferson R. Wilson

Christopher D. Witiw

Ahmad Galuta

Eve C. Tsai

Marcel F. Dvorak

Jijie Xu

Nader Fallah

Zeina Waheed

Melody Chen

Nicolas Dea

Nathan Evaniew

Vanessa Noonan

Brian Kwon

Toluyemi Malomo

Raphaële Charest-Morin

Scott Paquette

Tamir Ailon

Charlotte Dandurand

John Street

Charles G. Fisher

Nicolas Dea

Manraj Heran

Marcel Dvorak

Peter Coyte

Brian Chan

Armaan Malhotra

Rebecca Hancock-Howard

Jefferson Wilson

Christopher Witiw

Jordan Squair

Viviana Aureli

Nicholas James

Lea Bole-Feysot

Inssia Dewany

Nicolas Hankov

Laetitia Baud

Anna Leonhartsberger

Kristina Sveistyte

Michael Skinnider

Matthieu Gautier

Katia Galan

Maged Goubran

Jimmy Ravier

Frederic Merlos

Laura Batti

Stéphane Pagès

Nadia Bérard

Nadine Intering

Camille Varescon

Stefano Carda

Kay Bartholdi

Thomas Hutson

Claudia Kathe

Michael Hodara

Mark Anderson

Bogdan Draganski

Robin Demesmaeker

Leonie Asboth

Quentin Barraud

Jocelyne Bloch

Grégoire Courtine

Ryan Greene

Mustafa Nadi

Jacob Alant

Sean Barry

Andrew Glennie

Bill Oxner

Lutz Weise

Lisa Julien

Clara Lownie

Cumhur F.C. Öner

Charlotte Dandurand

Alexander Joeris

Klaus Schnake

Mark Phillips

Alexander R. Vaccaro

Richard Bransford

Eugen Cezar Popescu

Mohammed El-Sharkawi

Shanmuganathan Rajasekaran

Lorin M. Benneker

Greg D. Schroeder

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Justin Smith

Ferran Pellise

Zeeshan Sardar

Abdulrhman Alnasser

Uri Barak

Lior M. Elkaim

Thien Sa Hoang

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Daipayan Guha

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Alexander G. Weil

Michael H. Weber

Kashif Parvez

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Neda Naghdi

Maryse Fortin

Ran Ankory

Lisa Stallwood

Henry Ahn

Abdul Naeem

Deven Jhawar

Milad Moradi

Balraj Jhawar

Vithushan Surendran

Victoria Shi

Emily Cheung

Sophie Ngana

Muhammad A. Qureshi

Sunjay V. Sharma

Markian Pahuta

Daipayan Guha

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Canadian Journal of Surgery (publié)

SCIseg: Automatic Segmentation of Intramedullary Lesions in Spinal Cord Injury on T2-weighted MRI Scans

Enamundram Naga Karthik

Andrew C. Smith

Dario Pfyffer

Simon Schading-Sassenhausen

Lynn Farner

Kenneth A. Weber

Patrick Freund

The proposed deep learning model accurately segmented the spinal cord and spinal cord injury lesions in a diverse, multicenter dataset of T2… (voir plus)-weighted MRI scans.

2024-11-05

Radiology: Artificial Intelligence (inconnu)

Spinal cord evaluation in multiple sclerosis: clinical and radiological associations, present and future

B Mark Keegan

Martina Absinta

Eoin P Flanagan

Roland G Henry

Eric C Klawiter

Shannon Kolind

Stephen Krieger

Cornelia Laule

John A Lincoln

Steven Messina

Jiwon Oh

Nico Papinutto

Seth Aaron Smith

Anthony Traboulsee

2024-11-05

Brain Communications (publié)