Author

Michael C. Robitaille

United States Naval Research LaboratoryORCID 0000-0002-8445-7205Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioengineering· 1 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:clustering· 2 Assay:imaging· 2 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Approach:contrastive learning· 1 Approach:deep learning· 1 Assay:fluorescence / live-cell microscopy· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Jeff M. Byers· 2 shared Joseph A. ChristodoulidesiD· 2 shared Marc P. RaphaeliD· 2 shared Logan KaleriD· 1 shared Van K. LamiD· 1 shared

Activity by Year

2021-2025 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 10 mutual co-author links

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2 shared papersBioengineering

Jeff M. Byers

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2 papers

Recent·Most cited

A Self-Supervised Learning Approach for High Throughput and High Content Cell Segmentation

Van K. Lam, Jeff M. Byers, Michael C. Robitaille, Logan Kaler, Joseph A. Christodoulides, Marc P. Raphael

This paper introduces a self-supervised learning method for cell segmentation that outperforms Cellpose in accuracy and reduces reliance on labeled data and computational expertise.

Communications Biology · May 21, 2025Peer-reviewedBioengineering

A Self-Supervised Machine Learning Approach for Objective Live Cell Segmentation and Analysis

Michael C. Robitaille, Jeff M. Byers, Joseph A. Christodoulides, Marc P. Raphael

This paper introduces a self-supervised machine learning algorithm for automated live cell segmentation and analysis without user supervision or adjustable parameters.

bioRxiv · Jan 7, 2021 · PreprintBioinformatics