DEC 09, 2020 11:00 AM EST

Introduction to Image Processing for High-Content Screening

  • Data Scientist, Novartis Institutes for BioMedical Research

      Mark joined NIBR in 2016 as data scientist specializing in machine learning applied to high-content microscopy. He completed a Ph.D. in biomedical engineering at Vanderbilt University, a postdoctoral fellowship at Harvard University, followed by a staff scientist position in the Imaging Platform at the Broad Institute in Cambridge MA.


    Image-based screens require the use of automated microscopes which generates hundreds, if not thousands of images at a time. With such large image sets, automatic image analysis is more objective and quantitative and less tedious then visual inspection alone. This session will provide an overview of the basic concepts, methods and software used in automated image analysis, including which relevant image pixels, partitioning an image into cellular compartments and measuring interesting properties of these compartments.

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