DEC 14, 2017 07:00 AM PST
WEBINAR: Maximizing Sensitivity: The Impact of BSI-CMOS and Image-Processing in Scientific Imaging
SPONSORED BY: Photometrics
CONTINUING EDUCATION (CME/CE/CEU) CREDITS: P.A.C.E. CE | Florida CE
6 3 1379

Speakers:
  • Product Manager, Life Science Research Cameras, Photometrics
    Biography
      As the product manager for life science research cameras at Photometrics, Rachit Mohindra has been intimately involved with the development of scientific grade BSI-CMOS cameras that have made a significant impact in single molecule detection and super-resolution microscopy. His experience in managing the design intricacies of award-winning CMOS and EMCCD cameras has given him a unique perspective on emerging light detection technologies and their expected impact on life science microscopy.

    Abstract:

    DATE: December 14, 2017
    TIME: 7:00AM PT

    Recent breakthroughs in image sensor performance and signal processing have joined to enable new possibilities for live cell fluorescence microscopy. In this webinar, you will learn how to apply the newest camera innovations to your bioimaging applications, and correctly understand the trade-offs with each detection technology.

    Progress in life science research has both benefited from and pulled forward, innovation in image sensors. This is no more apparent than in scientific CMOS cameras that circumvent traditional sensor tradeoffs between frame rate, field-of-view and sensitivity. Several examples will be presented, showing how to prepare for the future when selecting an appropriate camera for current fluorescence microscopy methods.

    New breakthroughs in computational imaging and signal processing are also redefining how scientific cameras can move from image capture devices to assisting in the selecting and processing of important data. A vision for how this might be realized is presented. This includes application in particle tracking, super-resolution microscopy and improving signal-to-noise ratios with very low light imaging typical of live-cell microscopy.

    Learning Objectives:

    • be ready to make the best camera selection for your application
    • understand how on camera signal processing can benefit research
    • stay current with the latest improvements impacting scientific imaging

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