Author

S. Salama

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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Bioengineering· 1 Pathology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Organism:human· 2 Assay:imaging· 2 Approach:deep learning· 1 Approach:experimental assay· 1 Organism:plant (other)· 1 Research Focus:spatial domain detection· 1 Research Focus:trajectory inference· 1

Frequent Co-Authors

A. A. Pollen· 1 shared A. L. Martel· 1 shared A. Y. Panah· 1 shared D. Haussler· 1 shared E. A. Jung· 1 shared G. L. Mantalas· 1 shared H. R. Willsey· 1 shared J. A. Selberg· 1 shared

Activity by Year

2019-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperBioengineering

A. A. Pollen

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Author profile →

2 papers

Recent·Most cited

Development of a Low-Cost System for Simultaneous Longitudinal Biological Imaging

V. T. Ly, P. V. Baudin, P. Pansodtee, E. A. Jung, K. Voitiuk, Y. Rosen, H. R. Willsey, G. L. Mantalas, S. T. Seiler, J. A. Selberg, S. A. Cordero, J. M. Ross, M. Rolandi, A. A. Pollen, T. J. Nowakowski, , M. Teodorescu

The paper develops a low-cost imaging system for simultaneous longitudinal biological imaging and demonstrates its use across multiple organisms and tissue models.

bioRxiv · May 17, 2021Bioengineering

Automated and Manual Quantification of Tumour Cellularity in Digital Slides for Tumour Burden Assessment

S. Akbar, M. Peikari, S. Salama, A. Y. Panah, S. Nofech-Momes, A. L. Martel

This study compares automated and manual methods for quantifying tumour cellularity in digital slides, showing strong agreement between automated deep learning and expert assessments.

bioRxiv · Mar 12, 2019Pathology