Prof. Natan Tzvi Shaked

Dep. of Bio-Medical Engineering
מחלקה להנדסה ביו-רפואית סגל אקדמי בכיר
Prof. Natan Tzvi Shaked
Phone: 03-6407100
Fax: 03-6407100
Office: Multi-disciplinary Center, 410

Short Resume

Natan T. Shaked is a Professor and the Chair of the Department of Biomedical Engineering at Tel Aviv University, Israel. In 2011, he was a Visiting Assistant Professor in the Department of Biomedical Engineering at Duke University, Durham, North Carolina, USA, where he also did his postdoctoral research (2008-2010).

Research Interests

Prof. Shaked directs the Optical Microscopy, Nanoscopy and Interferometry (OMNI) research group. The group develops new experimental and analytical tools for 3D interferometric imaging of biological cells and thin elements that uniquely combine label-free wave-front sensing and imaging approaches, providing deep data by quantitative morphological and contents cellular imaging, with Artificial Intelligence (AI) by novel approaches for deep learning (Deep2Deep).

Specific subjects of interest:

Technology Development

  • Deep-learning platforms for biological cell classification [Papers]
  • Deep-learning platforms for biological cell virtual staining [Papers]
  • Rapid label-free wave-front imaging and sensing of biological cells [Papers]
  • Portable interferometric modules for clinical use [Papers]
  • 3D refractive-index live-cell tomography [Papers]
  • Interferometric nanoscopy [Papers]

Clinical Applications

  • Sperm selection for IVF [Papers]
  • Cancer cell analysis in liquid biopsies [Papers]

Achievements and Publications

Prof. Shaked is the author of more than 100 refereed journal papers and more than 170 conference papers, and several book chapters, patents, and an edited book on Biomedical Optical Phase Microscopy and Nanoscopy. He is the chair of the SPIE Label-Free Biomedical Imaging and Sensing (LBIS) annual conference in San Francisco, and a Fellow in the Optical Society of America (OSA) as well as in the SPIE. In 2015, he received the ERC starter grant.

Selected Publications:

  • G. Dardikman-YoffeS. K. MirskyI. Barnea, and N. T. Shaked, “High-resolution 4-D acquisition of freely swimming human sperm cells without staining,” Science Advances [IF 14.143], Vol. 6, No. 15, eaay7619, 2020 [PDFSupp MatVideo 1Video 2Video 3Video 4Video 5] [Link].
  • M. Rubin, O. Stein, N. A. TurkoY. NygateD. RoitshtainL. KarakoI. 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].
  • Y. N. NygateM. LeviS. K. MirskyN. A. TurkoM. RubinI. BarneaG. Dardikman-YoffeM. 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].
  • N. T. Shaked, V. Micó, M. Trusiak, A. Kus, and S. K. Mirsky, “Off-axis digital holographic multiplexing for rapid wave front acquisition and processing,” Advances in Optics and Photonics [IF 20.107], Vol. 12, Issue 3, pp. 556-611, 2020 [PDF] [Link].
  • M. Habaza, M. Kirschbaum, C. Guernth-Marschner, G. DardikmanI. Barnea, R. Korenstein, C. Duschl, and N. T. Shaked, “Rapid three-dimensional refractive-index imaging of live cells in suspension without labeling using dielectrophoretic cell rotation,” Advanced Science [IF 16.806], 1600205: 1-9, 2016 [PDF[Link] .
  • P. Girshovitz and N. T. Shaked, “Doubling the field of view in off-axis low-coherence interferometric imaging,” Nature – Light: Science and Applications (Nature LSA[IF 17.782], Vol. 3, e151, pp. 1-9, 2014 [PDFVideo 1Video 2] [Link].
  • K. Ben-YehudaS. K. MirskyM. LeviI. BarneaI. MeshulachS. KontenteD. BenvaishR. Cur-CycowiczY. 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].
  • S. Ben BaruchN. 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 6.6], Vol. 10, No. 12, 3353 2021 [PDF] [Link].

Full Journal Paper List - in his Group Website 

Google Scholar Profile

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