Total Variation-Based Reconstruction and Phase Retrieval for Diffraction Tomography

被引:3
作者
Beinert, Robert [1 ]
Quellmalz, Michael [1 ]
机构
[1] TU Berlin, Inst Math, D-10623 Berlin, Germany
关键词
phase retrieval; diffraction tomography; total variation; nonequispaced discrete Fourier transform; optical imaging; FAST FOURIER-TRANSFORMS; BUTTERFLY ALGORITHM; IMAGE; UNIQUENESS;
D O I
10.1137/22M1474382
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In optical diffraction tomography (ODT), the three-dimensional scattering potential of a microscopic object rotating around its center is recovered by a series of illuminations with coherent light. Reconstruction algorithms such as the filtered backpropagation require knowledge of the complex-valued wave at the measurement plane, whereas often only intensities, i.e., phaseless measurements, are available in practice. We propose a new reconstruction approach for ODT with unknown phase information based on three key ingredients. First, the light propagation is modeled using Born's approximation enabling us to use the Fourier diffraction theorem. Second, we stabilize the inversion of the nonuniform discrete Fourier transform via total variation regularization utilizing a primal-dual iteration, which also yields a novel numerical inversion formula for ODT with known phase. The third ingredient is a hybrid input-output scheme. We achieved convincing numerical results, which indicate that ODT with phaseless data is possible. The so-obtained 2-dimensional and 3-dimensional reconstructions are even comparable to the ones with known phase.
引用
收藏
页码:1373 / 1399
页数:27
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