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Optical diffraction tomography is a three-dimensional (3D) imaging technique that reconstructs the refractive index distribution of the sample using scattered lights from different illumination angles. Researchers from école Polytechnique Fédérale de Lausanne (EPFL) proposed a deep neural network to solve the optical scattering problem and used this neural network as a surrogate forward model in the iterative reconstruction of the optical diffraction tomography.