Author

T. Vicar

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

Biology Disciplines

Click to filter author papers

Bioengineering· 1 Biophysics· 1 Cell Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:cell type annotation· 3 Assay:imaging· 3 Approach:experimental assay· 2 Approach:machine learning (classical)· 1

Frequent Co-Authors

J. Gumulec· 3 shared M. Masarik· 3 shared I. Provaznik· 2 shared J. Chmelik· 2 shared J. Navratil· 2 shared L. Chmelikova· 2 shared R. Kolar· 2 shared V. Cmiel· 2 shared

Activity by Year

2019-2021 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

3 shared papersBiophysics

J. Gumulec

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Cancer Cells Viscoelasticity Measurement by Quantitative Phase and Flow Stress Induction

T. Vicar, J. Gumulec, J. Chmelik, J. Navratil, R. Kolar, L. Chmelikova, V. Cmiel, I. Provaznik, M. Masarik

This paper introduces a method to measure cancer cell viscoelasticity using quantitative phase imaging and fluid flow-induced shear stress, demonstrating reliable high-throughput measurements of mechanical properties and cell morphology.

bioRxiv · Aug 5, 2021Biophysics

Parametric Deconvolution for Cancer Cells Viscoelasticity Measurements from Quantitative Phase Images

T. Vicar, J. Gumulec, R. Kolar, J. Chmelik, J. Navratil, L. Chmelikova, V. Cmiel, I. Provaznik, M. Masarik

This paper develops a parametric deconvolution method to improve the accuracy of viscoelastic property measurements in cancer cells using quantitative phase imaging by correcting flow system distortions.

bioRxiv · Apr 6, 2021 · PreprintBioengineering

Detection and characterization of apoptotic and necrotic cell death by time-lapse quantitative phase image analysis

T. Vicar, M. Raudenska, J. Gumulec, M. Masarik, J. Balvan

This study introduces a method using quantitative phase imaging and machine learning to detect and classify apoptotic and necrotic cell death with 75.4% accuracy.

bioRxiv · Mar 27, 2019Cell Biology