Speaker
Description
The point spread function (PSF) of an imaging system is the system's response to a point source. To encode additional information in microscopy images, we employ PSF engineering – namely, a physical modification of the standard PSF of the microscope by additional optical elements that perform wavefront shaping. In this talk I will describe how this method enables unprecedented capabilities in localization microscopy; specific applications include dense fluorescent molecule fitting for 3D super-resolution microscopy, multicolor imaging from grayscale data, volumetric multi-particle tracking/imaging, dynamic surface profiling, and high-throughput in-flow colocalization in live cells. I will specifically describe how deep-learning can help us design optimal PSFs for various tasks by joint optimization of the optical encoder + algorithmic (neural net based) decoder. Recent results on additive-manufacturing of highly precise optics will be discussed as well.