APR 18, 2019 9:00 AM PDT

Deep Learning in Optics

Sponsored by: Leica Microsystems
  • Professor, UCLA
      Dr. Ozcan is the Chancellor's Professor at UCLA and an HHMI Professor with the Howard Hughes Medical Institute, leading the Bio- and Nano-Photonics Laboratory at UCLA School of Engineering and is also the Associate Director of the California NanoSystems Institute. Dr. Ozcan is elected Fellow of the National Academy of Inventors (NAI) and holds 39 issued patents and >20 pending patent applications and is also the author of one book and the co-author of >700 peer-reviewed publications in major scientific journals and conferences. Dr. Ozcan is the founder and a member of the Board of Directors of Lucendi Inc. as well as Holomic/Cellmic LLC, which was named a Technology Pioneer by The World Economic Forum in 2015. Dr. Ozcan is also a Fellow of the American Association for the Advancement of Science (AAAS), the International Photonics Society (SPIE), the Optical Society of America (OSA), the American Institute for Medical and Biological Engineering (AIMBE), the Institute of Electrical and Electronics Engineers (IEEE), the Royal Society of Chemistry (RSC), and the Guggenheim Foundation, and has received major awards including the Presidential Early Career Award for Scientists and Engineers, International Commission for Optics Prize, Biophotonics Technology Innovator Award, Rahmi M. Koc Science Medal, International Photonics Society Early Career Achievement Award, Army Young Investigator Award, NSF CAREER Award, NIH Director's New Innovator Award, Navy Young Investigator Award, IEEE Photonics Society Young Investigator Award and Distinguished Lecturer Award, National Geographic Emerging Explorer Award, National Academy of Engineering The Grainger Foundation Frontiers of Engineering Award and MIT's TR35 Award for his seminal contributions to computational imaging, sensing and diagnostics.
    • Graduate Student, UCLA
        Hongda Wang is a M.S./Ph.D. student of the Electrical and Computer Engineering Department at the University of California, Los Angeles (UCLA). He received his Bachelor of Science in Physics from the School of Physics in Peking University in 2015, and Master of Science in Electrical and Computer Engineering from the Henry Samueli School of Engineering and Applied Science in UCLA. His research interest is biomedical imaging and image processing techniques for novel imaging methods and applications. Currently, he's focusing on high-throughput, high-resolution biomedical microscopy in the Bio-photonics Lab at UCLA.
      • Adjunct Professor, UCLA
          Dr. Rivenson is an adjunct professor in the Department of Electrical and Computer Engineering, UCLA. His current research interests include computational imaging and sensing for biomedical, life sciences and environmental applications, and physics inspired machine learning. Dr. Rivenson has co-authored ~ 100 peer-reviewed works in scientific journals, conferences and book chapters. Dr. Rivenson is a Member of the Optical Society of America (OSA), Society of Photographic Instrumentation Engineers (SPIE), the Digital Pathology Association (DPA) and an Associate Member of the IEEE Bio Imaging and Signal Processing (BISP) technical committee.
          His research in the field of computational imaging has received numerous awards and distinctions.
        • Research Scientist, UCLA
            Dr. Bentolila is Director of the Advanced Light Microscopy/Spectroscopy Laboratory, the Macro-Scale Imaging Laboratory, the Leica Microsystems Center of Excellence and a Research Scientist at the California NanoSystems Institute at UCLA. Dr. Bentolila's long-standing research interest focuses on the application of nanotechnology and advanced light microscopy techniques to biology and medicine. Towards this goal, Dr. Bentolila has developed novel fluorescent probes and assembled a unique collection of custom-built and commercial optical microscopes used for the study of macromolecules, cellular dynamics and nanoscale characterization of biomaterials. Since joining UCLA in 2002, Dr. Bentolila has received continuous federal and institutional funding to develop multi-disciplinary research programs and support a state-of-the-art optical microscopy Technology Center that fosters innovation across disciplines and facilitate university collaborations with industry. Dr. Bentolila is the recipient of several awards including the European Molecular Biology Organization and the Burroughs Wellcome Fund.

          DATE:   April 18, 2019
          TIME:    9:00am PDT, 12:00pm EDT
          Researchers at the California NanoSystems Institute (CNSI) at UCLA have created a novel, data-driven, deep learning framework that allows for the generation of super-resolution images directly from images acquired on conventional, diffraction-limited microscopes. This is completed without prior knowledge about the sample and/or the image formation process to super-resolve microscopic images beyond the diffraction limit. The deep network output is extremely fast, without any iterations or parameter searches. In another demonstration, the researchers have used a deep neural network to perform virtual histological staining of a label free tissue sections, using a single autofluorescence image. This transformation, which uses only the endogenous contrast of the tissue section, was applied to multiple types of tissues and stains and blindly validated by board a panel of pathologists.
          These results represent an important step towards computational microscopy and illustrate some of the potential machine learning to the field.
          Learning Objectives:
          • Understanding of computational microscopy principles
          • Using deep learning algorithms to generate super-resolution images
          • Using deep learning algorithms for virtual staining


          LabRoots is approved as a provider of continuing education programs in the clinical laboratory sciences by the ASCLS P.A.C.E. ® Program. By attending this webinar, you can earn 1 Continuing Education credit once you have viewed the webinar in its entirety.

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          APR 18, 2019 9:00 AM PDT

          Deep Learning in Optics

          Sponsored by: Leica Microsystems


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