Computational Deep Learning Microscopy
Hosted By: Photonic Detection Technical Group
21 March 2019, 14:00 - 15:00
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The emergence of deep learning as applied to computational microscopy, with the unique challenges and opportunities created by this framework will be discussed in this webinar, hosted by the OSA Photonic Detection Technical Group. Dr. Yair Rivenson from the University of California, Los Angeles, will discuss opportunities relating to enhancement of brightfield benchtop microscope images, super-resolve beyond the diffraction limit and perform cross-modality imaging in fluorescence microscopy, i.e. transforming an image acquired using one microscope to match an image acquired using a different microscopic imaging modality, while improving the signal-to-noise ratio, throughput, and reducing phototoxicity.
The application of virtual histopathology staining, where a deep network can learn how to digitally stain a single, label-free (unstained), autofluorescent image to match the same image of the tissue section as it would have been histologically stained and imaged using a brightfield microscope. By that, this technology enables a paradigm shift in the diagnostic workflow, bypassing the laborious and lengthy process of histochemical staining, while allowing tissue preservation. Finally, Dr. Rivenson will demonstrate how deep learning can be used to substantially increase the throughput of coherent (such as holographic) imaging systems and demonstrate some of the opportunities that deep learning brings to that field.
What You Will Learn:
- This webinar will provide an overview of how the rapidly developing field of deep learning is impacting biomedical imaging and simplifying diagnostic work-flows.
Who Should Attend:
- The presentation will be of interest to researchers interested in the cross-disciplinary fields of deep learning, photonic detection and biomedical optics including spectroscopy, holography, OCT, diffractive optics, tissue imaging, and bio-optics.
Dr. Yair Rivenson
Dr. Yair Rivenson is a Marie-Skolodwska-Curie fellow in the Ozcan research group. His main research interest is in imaging sciences, including computational imaging theory and applications, combining the physical understanding of the system along with mathematical modeling and applying recent signal processing methodologies. Rivenson is the co-author of 45 refereed journals and conference papers (8 of them invited), 2 book chapters and 1 publication in special edition of Optics and Photonics News 2012 annual review. He has won several prestigious awards, including the ERC Marie Skolodwska-Curie Global Fellowship, 5 Ben-Gurion inter-University awards, Chancellor's Award for Postdoctoral Research, and 3 Israeli National Awards.