Author

Etienne St‐Onge

Université de SherbrookeORCID 0000-0002-9734-4947Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 3 Organism:human· 3 Assay:imaging· 3 Approach:statistical model· 3 Research Focus:dimensionality reduction· 2 Approach:experimental assay· 2 Research Focus:cell type annotation· 1 Research Focus:database / resource· 1

Frequent Co-Authors

Maxime DescoteauxiD· 4 shared Alan Charles EvansiD· 2 shared Guillaume TheaudiD· 2 shared Noor Al‐SharifiD· 2 shared Alexandra Livadas· 1 shared Alzheimer’s Disease Neuroimaging Initiative· 1 shared Ana Laura ManeraiD· 1 shared Arnaud BoréiD· 1 shared

Activity by Year

2020-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 15 mutual co-author links

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4 shared papersNeuroscience

Maxime DescoteauxORCID

Mutual co-authors in cluster

Author profile →

5 papers

Recent·Most cited

QRATER: a collaborative and centralized imaging quality control web-based application.

Sofia Fernandez‐Lozano, Mahsa Dadar, Cassandra Morrison, Ana Laura Manera, Daniel Andrews, Reza Rajabli, Victoria Madge, Etienne St‐Onge, N. Shaffie, Alexandra Livadas, Vladimir Fonov, D. Louis Collins, Alzheimer’s Disease Neuroimaging Initiative

QRATER is a web-based QC tool for neuroimaging that enables rating of QC images, showing varying time and agreement across tasks and rater experience.

Aperture Neuro · Jun 18, 2024Peer-reviewedBioinformatics

TractoInferno: A large-scale, open-source, multi-site database for machine learning dMRI tractography

Philippe Poulin, Guillaume Theaud, François Rheault, Etienne St‐Onge, Arnaud Boré, Emmanuelle Renauld, Louis De Beaumont, Samuel Guay, Pierre‐Marc Jodoin, Maxime Descoteaux

TractoInferno provides a large-scale, multi-site database for benchmarking machine learning tractography methods using standardized data and evaluation protocols.

Scientific Data · Nov 25, 2022Peer-reviewedNeuroscience

Structural connectome fingerprinting and age prediction in pediatric development: assessing voxel- and surface-based white matter connectivity

Noor Al‐Sharif, Etienne St‐Onge, Jacob W. Vogel, Maxime Descoteaux, Alan Charles Evans

The paper compares voxel- and surface-based methods for generating structural connectomes, finding voxel-based methods marginally better for age prediction and individual representation.

bioRxiv · Feb 19, 2021 · PreprintNeuroscience

Processing the diffusion-weighted magnetic resonance imaging of the PING dataset

Noor Al‐Sharif, Etienne St‐Onge, Guillaume Theaud, Alan Charles Evans, Maxime Descoteaux

This paper processes diffusion-weighted MRI data from the PING dataset to improve connectomic analysis through advanced diffusion metrics and multimodal integration.

bioRxiv · Nov 24, 2020 · PreprintNeuroscience

Surface-Based Connectivity Integration

Martin Cole, Kyle D. Murray, Etienne St‐Onge, Benjamin B. Risk, Jianhui Zhong, Giovanni Schifitto, Maxime Descoteaux, Zhengwu Zhang

This paper introduces a framework called surface-based connectivity integration (SBCI) to analyze structural and functional brain connectivity by using the white surface and shows it creates reproducible biomarkers reflecting SC-FC similarity.

bioRxiv · Jul 1, 2020 · PreprintNeuroscience