Author

J. U. Becker

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Pathology· 2

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Approach:deep learning· 2 Assay:imaging· 2 Research Focus:benchmarking· 1 Research Focus:clustering· 1 Approach:experimental assay· 1 Organism:mouse· 1 Research Focus:spatial domain detection· 1

Frequent Co-Authors

B. R. Lutnick· 2 shared D. Manthey· 2 shared J. E. Zuckerman· 2 shared K. Y. Jen· 2 shared L. Rodrigues· 2 shared P. Sarder· 2 shared A. J. Gallan· 1 shared A. Z. Rosenberg· 1 shared

Activity by Year

2021-2021 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersPathology

B. R. Lutnick

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Author profile →

2 papers

Recent·Most cited

A tool for federated training of segmentation models on whole slide images.

B. R. Lutnick, D. Manthey, J. U. Becker, J. E. Zuckerman, L. Rodrigues, K. Y. Jen, P. Sarder

The paper demonstrates that federated learning can train segmentation models on whole slide images with performance comparable to centralized training across multiple institutions.

bioRxiv · Aug 17, 2021Pathology

A user-friendly tool for cloud-based whole slide image segmentation, with examples from renal histopathology

B. R. Lutnick, D. Manthey, J. U. Becker, B. Ginley, K. Moos, J. E. Zuckerman, L. Rodrigues, A. J. Gallan, L. Barisoni, C. E. Alpers, X. Wang, K. Myakala, B. A. Jones, M. Levi, J. B. Kopp, , Kidney Precision Medicine Project

Histo-Cloud is a cloud-based tool for whole slide image segmentation that simplifies access for non-experts, demonstrating its use in renal histopathology.

bioRxiv · Aug 16, 2021Pathology