AI for Cell Virtual Staining, Classification and Fast Processing

Bold-text authors are OMNI group members.

AI for Virtual Staining of Biological Cells

  • Y. N. Nygate, M. Levi, S. K. Mirsky, N. A. Turko, M. Rubin, I. Barnea, G. Dardikman-Yoffe, M. Haifler, A. Shalev, and N. T. Shaked, “Holographic virtual staining of individual biological cells,” Proceedings of the National Academy of Sciences USA (PNAS) [IF 11.205], Vol. 117, No. 17, pp. 9223-9231, 2020 [PDF] [Link].
  • K. Ben-Yehuda, S. K. Mirsky, M. Levi, I. Barnea, I. Meshulach, S. Kontente, D. Benvaish, R. Cur-Cycowicz, Y. N. Nygate, and N. T. Shaked, “Simultaneous morphology, motility and fragmentation analysis of live individual sperm cells for male fertility evaluation,” Accepted to Advanced Intelligent Systems, 2021 [PDFVideo 1, Video 2[Link].

AI for Automatic Classification of Biological Cells

  • M. Rubin, O. Stein, N. A. Turko, Y. Nygate, D. Roitshtain, L. Karako, I. Barnea, R. Giryes, and N. T. Shaked, “TOP-GAN: Stain-free cancer cell classification using deep learning with a small training set,” Medical Image Analysis [IF 8.545], Vol. 57, pp. 176-185, 2019 [Link].
  • S. Ben Baruch, N. Rotman-Nativ, A. Baram, H. Greenspan, and N. T. Shaked, “Cancer-cell deep-learning classification by integrating quantitative-phase spatial and temporal fluctuations,” Cells [IF 7.666], Vol. 10, No. 12, 3353 2021 [PDF] [Link].
  • N. Rotman-Nativ and N. T. Shaked, “Live cancer cell classification based on quantitative phase spatial fluctuations and deep learning with a small training set,” Frontiers in Physics, Vol. 9, 754897, 2021 [PDF] [Link].
  • N. Nissim, M. Dudaie, I. Barnea, and N. T. Shaked, “Real-time stain-free classification of cancer cells and blood cells using interferometric phase microscopy and machine learning,” Cytometry A, Vol. 99, Issue 5, pp. 511-523, 2021 [Link].
  • S. K. Mirsky, I. Barnea, M. Levi, H. Greenspan, and N. T. Shaked, “Automated analysis of individual sperm cells using stain-free interferometric phase microscopy and machine learning,” Cytometry Part A, Vol. 91, Issue 9, pp. 893-900, 2017 [Link].
  • D. Roitshtain, L. Wolbromsky, E. Bal, H. Greenspan, L. Satterwhite, and N. T. Shaked, “Quantitative phase microscopy spatial signatures of cancer cells,” Cytometry Part A, Vol. 91, Issue 5, pp. 482-493, 2017 [Link].

AI for Rapid Processing of Quantitative Phase Images of Biological Cells

  • G. Dardikman-Yoffe, D. Roitshtain, S. K. Mirsky, N. A. Turko, M. Habaza, and N. T. Shaked, “PhUn-Net: ready-to-use neural network for unwrapping quantitative phase images of biological cells,” Biomedical Optics Express, Vol. 11, No. 2, pp. 1107-1121, 2020 [Link].



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