Author

Daniel Lichau

Thermo Fisher Scientific (United States)

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· 1

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 Edward M. SchwarziD· 1 shared H. Mark KenneyiD· 1 shared Hani A. AwadiD· 1 shared Lindsay SchnuriD· 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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Author profile →

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