Author

Solène‐Florence Kammerer‐Jacquet

Centre Hospitalier Universitaire de RennesORCID 0000-0002-6623-741XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 1 Approach:deep learning· 1 Organism:human· 1 Assay:imaging· 1

Frequent Co-Authors

Christine SaganiD· 1 shared Claire S. ToquetiD· 1 shared Delphine LoussouarniD· 1 shared Matthias GriebeliD· 1 shared Nathalie C. Rioux-LeclercqiD· 1 shared Raphaël BourgadeiD· 1 shared Sébastien Henno· 1 shared Tanguy PerenneciD· 1 shared

Activity by Year

2022-2022 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 28 mutual co-author links

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1 shared paperBioinformatics

Christine SaganORCID

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1 paper

Recent·Most cited

BioinformaticsbioRxivPreprintFeb 7, 2022

A deep learning model trained on only eight whole-slide images accurately segments tumors: wise data use versus big data

Tanguy Perennec, Raphaël Bourgade, Sébastien Henno…·Matthias Griebel

This paper develops a deep learning model that accurately segments tumors using only eight whole-slide images, showing that small, well-annotated datasets can achieve high performance in medical imaging.

1 citation

humanimaging

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