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Darina Roitshtain

Showing results (1-10 of 5) with videos related to

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Optics Letters|May 14, 2016
Flipping interferometry and its application for quantitative phase microscopy in a micro-channelDarina Roitshtain, Nir A Turko, Bahram Javidi, et al.
Journal of Biomedical Optics|June 22, 2017
Dynamic measurements of flowing cells labeled by gold nanoparticles using full-field photothermal interferometric imagingNir A Turko, Darina Roitshtain, Omry Blum, et al.
Cytometry. Part a : the Journal of the International Society for Analytical Cytology|April 21, 2017
Quantitative phase microscopy spatial signatures of cancer cellsDarina Roitshtain, Lauren Wolbromsky, Evgeny Bal, et al.
Biomedical Optics Express|March 25, 2020
PhUn-Net: ready-to-use neural network for unwrapping quantitative phase images of biological cellsGili Dardikman-Yoffe, Darina Roitshtain, Simcha K Mirsky, et al.
Medical Image Analysis|July 21, 2019
TOP-GAN: Stain-free cancer cell classification using deep learning with a small training setMoran Rubin, Omer Stein, Nir A Turko, et al.
Pageof 1

Showing results (1-10 of 5) with videos related to

Sort By:
Pageof 1
Optics Letters|May 14, 2016
Flipping interferometry and its application for quantitative phase microscopy in a micro-channelDarina Roitshtain, Nir A Turko, Bahram Javidi, et al.
Journal of Biomedical Optics|June 22, 2017
Dynamic measurements of flowing cells labeled by gold nanoparticles using full-field photothermal interferometric imagingNir A Turko, Darina Roitshtain, Omry Blum, et al.
Cytometry. Part a : the Journal of the International Society for Analytical Cytology|April 21, 2017
Quantitative phase microscopy spatial signatures of cancer cellsDarina Roitshtain, Lauren Wolbromsky, Evgeny Bal, et al.
Biomedical Optics Express|March 25, 2020
PhUn-Net: ready-to-use neural network for unwrapping quantitative phase images of biological cellsGili Dardikman-Yoffe, Darina Roitshtain, Simcha K Mirsky, et al.
Medical Image Analysis|July 21, 2019
TOP-GAN: Stain-free cancer cell classification using deep learning with a small training setMoran Rubin, Omer Stein, Nir A Turko, et al.
Pageof 1