Author

Alexandre Laurent

Centre National de la Recherche ScientifiqueORCID 0000-0001-5198-6955Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 3

Signature Assays, Organisms & Methods

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

Frequent Co-Authors

Ami TsuchidaiD· 3 shared Bernard M. MazoyeriD· 3 shared Christophe TzourioiD· 3 shared Antonietta PepeiD· 2 shared Fabrice CrivelloiD· 2 shared Laurent PetitiD· 2 shared Marc JoliotiD· 2 shared Naka Beguedou· 2 shared

Activity by Year

2021-2021 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersNeuroscience

Ami TsuchidaORCID

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3 papers

Recent·Most cited

NeuroscienceFrontiers in Systems NeurosciencePeer-reviewedAug 3, 2021

Changes in regional white matter volumetry and microstructure during the post-adolescence period: a cross-sectional study of a cohort of 1,713 university students

Ami Tsuchida, Alexandre Laurent, Fabrice Crivello…·Bernard M. Mazoyer

This study examines regional changes in white matter volume and microstructure in young adults using MRI data from 1,713 university students, revealing age-related variations in microstructural properties.

12 citations

humanimaging

𝕏 PostBluesky

NeuroscienceBrain Structure and FunctionPeer-reviewedJul 20, 2021

The MRi-Share database: brain imaging in a cross-sectional cohort of 1,870 university students

Ami Tsuchida, Alexandre Laurent, Fabrice Crivello…·Bernard M. Mazoyer

The paper introduces the MRi-Share database, a multi-modal brain MRI dataset of 1,870 young adults, and presents preliminary findings on age and sex associations with brain phenotypes.

36 citations

humanimaging

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NeuroscienceFrontiers in NeuroinformaticsPeer-reviewedJun 18, 2021

3D segmentation of perivascular spaces on T1-weighted 3 Tesla MR images with a convolutional autoencoder and a U-shaped neural network

Philippe Boutinaud, Ami Tsuchida, Alexandre Laurent…·Marc Joliot

This paper develops a deep learning algorithm for 3D segmentation of perivascular spaces in MRI data, achieving high accuracy and demonstrating interoperability across scanners.

84 citations

imagingdeep learning

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