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Iterative optimization in tomographic deconvolution phase microscopy

Abstract

Tomographic deconvolution phase microscopy (TDPM) is a three-dimensional (3D) quantitative phase imaging (QPI) method using partially coherent light that can be implemented on a commercial microscope platform. However, the measurement procedure is relatively time-consuming because it requires many illumination angles. In the present work, an edge-preserving iterative optimization algorithm is presented and applied to TDPM, so that the required number of illumination angles is reduced from 15 to 3, while the measurement accuracy remains high. In addition, the iterative algorithm does not require matrix representation of operators, so the memory requirement is correspondingly reduced.

© 2018 Optical Society of America

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