Author

Mélanie Garcia

Harvard UniversityORCID 0000-0003-2263-1375Unclaimed 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· 2 Approach:statistical model· 2 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1 Organism:human· 1 Assay:imaging· 1

Frequent Co-Authors

Ariel RokemiD· 1 shared Céline ProvinsiD· 1 shared Clare A. M. KellyiD· 1 shared Eilidh MacNicoliD· 1 shared Jamie K. LiiD· 1 shared Jon Haitz LegarretaiD· 1 shared Martin NørgaardiD· 1 shared McKenzie Paige HageniD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperNeuroscience

Ariel RokemORCID

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2 papers

Recent·Most cited

NeuroscienceNature ProtocolsPeer-reviewedMay 11, 2026

Quality assessment and control of unprocessed anatomical, functional, and diffusion MRI of the human brain using MRIQC

McKenzie Paige Hagen, Céline Provins, Eilidh MacNicol…·Oscar Estéban

The paper introduces a protocol for assessing and controlling MRI data quality using MRIQC software, focusing on anatomical, functional, and diffusion MRI scans of the human brain.

DOI 10.1038/s41596-026-01352-y

humanstatistical model

𝕏 PostBluesky

NeuroscienceImaging NeurosciencePeer-reviewedJan 1, 2024

BrainQCNet: a Deep Learning attention-based model for the automated detection of artifacts in brain structural MRI scans.

Mélanie Garcia, Nico U.F. Dosenbach, Clare A. M. Kelly

The paper introduces BrainQCNet, a deep learning model for automated artifact detection in brain structural MRI scans, achieving high accuracy and fast processing times.

9 citations

imagingdeep learning

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