Author

Lindsay Schnur

University of Rochester MedicineORCID 0000-0002-3040-583XUnclaimed 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:clustering· 1 Approach:deep learning· 1 Assay:imaging· 1 Organism:mouse· 1

Frequent Co-Authors

Christopher T. RitchliniD· 1 shared Daniel Lichau· 1 shared Edward M. SchwarziD· 1 shared H. Mark KenneyiD· 1 shared Hani A. AwadiD· 1 shared Rémi Blanc· 1 shared Richard D. BelliD· 1 shared Ronald W. WoodiD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 28 mutual co-author links

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1 shared paperPathology

Christopher T. RitchlinORCID

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1 paper

Recent·Most cited

Automated Joint Space Detection Improves Bone Segmentation Accuracy

H. Mark Kenney, Daniel Lichau, Rémi Blanc, Lindsay Schnur, Richard D. Bell, Christopher T. Ritchlin, Edward M. Schwarz, Hani A. Awad, Ronald W. Wood

This paper introduces a deep learning model for automated joint space detection in micro-CT images of mouse paws, significantly improving segmentation accuracy compared to semi-automated methods.

Journal of Visualized Experiments · Nov 28, 2025Peer-reviewedPathology