Author

Franklin W. Feingold

Stanford UniversityORCID 0000-0002-6533-2909Unclaimed 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 Research Focus:database / resource· 2 Approach:deep learning· 1 Approach:experimental assay· 1 Organism:multiple species· 1

Frequent Co-Authors

Christopher Johnson MarkiewicziD· 3 shared Krzysztof J. GorgolewskiiD· 2 shared Oscar EstébaniD· 2 shared Ross W. BlairiD· 2 shared Russell Alan PoldrackiD· 2 shared Adam G. ThomasiD· 1 shared Alessio GiacomeliD· 1 shared Alexandre RoutieriD· 1 shared

Activity by Year

2021-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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3 shared papersNeuroscience

Christopher Johnson MarkiewiczORCID

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Author profile →

3 papers

Recent·Most cited

PET-BIDS, an extension to the brain imaging data structure for positron emission tomography

Martin Nørgaard, Granville James Matheson, Hanne Demant Hansen, Adam G. Thomas, Graham E. Searle, Gaia Rizzo, Mattia Veronese, Alessio Giacomel, Maqsood M. Yaqub, Mattéo Tonietto, Thomas Funck, Ashley Gillman, Hugo Boniface, Alexandre Routier, Jelle R. Dalenberg, , Melanie Ganz

The paper introduces PET-BIDS, an extension of the BIDS standard for PET data, and provides curated datasets and tools for its use.

Scientific Data · Mar 2, 2022Peer-reviewedNeuroscience

OpenNeuro: An open resource for sharing of neuroimaging data

Christopher Johnson Markiewicz, Krzysztof J. Gorgolewski, Franklin W. Feingold, Ross W. Blair, Yaroslav O. Halchenko, Eric Miller, Nell Hardcastle, Joe Wexler, Oscar Estéban, Mathias Goncalves, Anita S. Jwa, Russell Alan Poldrack

OpenNeuro is an open archive for sharing brain imaging data following FAIR principles, hosting over 600 datasets from 20,000 participants across species and modalities, with over 150 publications citing its data.

eLife · Oct 18, 2021Peer-reviewedNeuroscience

High-sensitivity detection of facial features on MRI brain scans with a convolutional network

Shashank Bansal, Avinash Kori, Wazeer Deen Zulfikar, Joseph Wexler, Christopher Johnson Markiewicz, Franklin W. Feingold, Russell Alan Poldrack, Oscar Estéban

The paper introduces a convolutional neural network to detect defaced facial features in MRI brain scans, achieving high accuracy and sensitivity using data augmentation.

bioRxiv · Apr 25, 2021 · PreprintNeuroscience