Author

Hervé Lombaert

ORCID 0000-0002-3352-7533Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Approach:deep learning· 1 Organism:human· 1 Assay:imaging· 1

Frequent Co-Authors

Abdulah FawaziD· 1 shared Amir AlansaryiD· 1 shared Anthony David EdwardsiD· 1 shared Bonnie AlexanderiD· 1 shared Cher BassiD· 1 shared Chris L. AdamsoniD· 1 shared Christian DesrosiersiD· 1 shared Daniel RueckertiD· 1 shared

Activity by Year

2021-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperNeuroscience

Abdulah FawazORCID

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1 paper

Recent·Most cited

Benchmarking Geometric Deep Learning for Cortical Segmentation and Neurodevelopmental Phenotype Prediction

Abdulah Fawaz, Logan Z. J. Williams, Amir Alansary, Cher Bass, Karthik Kuduva Gopinath, Mariana da Silva, Simon Dahan, Chris L. Adamson, Bonnie Alexander, Deanne Kim Thompson, Gareth Ball, Christian Desrosiers, Hervé Lombaert, Daniel Rueckert, Anthony David Edwards, Emma C. Robinson

This paper benchmarks geometric and traditional deep learning models for cortical segmentation and neurodevelopmental phenotype prediction using neonatal cortical surface data.

bioRxiv · Dec 1, 2021 · PreprintNeuroscience