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Deep-learning-assisted snapshot optical tomography for microscopic volume prediction: a simulation study

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Abstract

In this simulation study, we demonstrate fast-yet-accurate volume measurement of microscopic objects by combining snapshot optical tomography and deep learning. Snapshot optical tomography simultaneously collects a multitude of projection images and thus can perform 3D imaging in a single snapshot. However, as with other wide-field microscopy techniques, it suffers from the missing-cone problem, which can seriously degrade the quality of 3D reconstruction. We use deep learning to generate a volume prediction from 2D projection images bypassing the 3D reconstruction.

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Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

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