Optical diffraction tomography with deep field match optimization (Conference Presentation)

As a label-free and quantitative imaging technique, optical diffraction tomography has been widely used in biological imaging. However, it is typically limited to weakly-scattering objects. To overcome this limitation, optimization algorithms based on minimizing field differences at the exit/observation plane, including total variation regularization, have been proposed and demonstrated. We propose a novel optimization algorithm to generalize field discrepancies from one plane to multiple planes throughout the scattering area. We numerically demonstrate that minimizing the field discrepancies at multiple planes instead of only one plane improves the robustness and accuracy of reconstructing multiply-scattering objects, without sacrificing the computational efficiency.