Deep learning based computational microscopy in scattering media (Conference Presentation)

Lei Tian

doi:10.1117/12.2550412

11 March 2020 Deep learning based computational microscopy in scattering media (Conference Presentation)

Lei Tian

Proceedings Volume 11248, Adaptive Optics and Wavefront Control for Biological Systems VI; 112480A (2020) https://doi.org/10.1117/12.2550412
Event: SPIE BiOS, 2020, San Francisco, California, United States

Abstract

I will discuss our efforts in developing computational microscopy techniques that can provide improved robustness and scalability to multiple scattering problems. First, I will discuss a new model for quantifying the effects of anisotropic scattering on image quality degradation. In particular, I will illustrate how to quantitatively relate the macroscopic scattering properties to the microscopic parameters used in the model. Next, I will discuss a deep learning approach to invert the effect of scattering. Particular emphasis will be placed on the scalability of this approach and how the model can be generalizable to different objects/media by extracting statistically invariant information.

Conference Presentation

Citation Download Citation

Lei Tian "Deep learning based computational microscopy in scattering media (Conference Presentation)", Proc. SPIE 11248, Adaptive Optics and Wavefront Control for Biological Systems VI, 112480A (11 March 2020); https://doi.org/10.1117/12.2550412

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