Computational bio-imaging via inverse scattering

Optical imaging is a major research tool in the basic sciences, and is the only imaging modality that routinely enables non-ionized imaging with subcellular spatial resolutions and high imaging speeds. In biological imaging applications, however, optical imaging is limited by tissue scattering to short imaging depths. This prevents large-scale bio-imaging by allowing visualization of only the outer superficial layers of an organism, or specific components isolated from within the organism and prepared in-vitro. I present recent developments in our lab that design inverse-scattering methods to computationally unscramble the effects of scattering in optically thick samples. I will specifically discuss 1) novel computational microscope system designs that enable novel methods for data collection; and 2) the design and practical implementation of large-scale computational nonlinear and nonconvex frameworks that enable robust inverse-scattering. Real-world bio-imaging will be demonstrated on multiple-scattering organisms popularly used in the basic-sciences.