In localization microscopy, the positions of individual nanoscale point emitters (e.g. fluorescent molecules) are determined at high precision from their point-spread functions (PSFs). This enables highly precise single/multiple-particle-tracking, as well as super-resolution microscopy, namely single molecule localization microscopy (SMLM).
In this talk I will describe advances to localization microscopy that we have recently achieved using deep learning, both in analysis (image processing) and in optimal imaging-system design. Specific topics to be discussed include: volumetric (3D) SMLM and single particle tracking by deep-learning-based PSF engineering, high-throughput in-flow colocalization in live cells, dynamic SMLM (blinking-to-video), and optical genome mapping.
A novel method for additive-manufacturing of phase masks for wavefront shaping will also be discussed.
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