Paper
18 December 2023 Impact of boundary conditions on accuracy of quantitative phase imaging
Yao Jin, Yefeng Shu, Yuzhen Zhang, Jiasong Sun, Chao Zuo
Author Affiliations +
Proceedings Volume 12967, AOPC 2023: Computing Imaging Technology; 129670C (2023) https://doi.org/10.1117/12.3007991
Event: Applied Optics and Photonics China 2023 (AOPC2023), 2023, Beijing, China
Abstract
Quantitative phase imaging (QPI) has gained extensive attention in the field of biomedical imaging and life sciences due to its unique ability to quantify the important physical characteristics of living cells and tissues without labeling. However, boundary conditions have always seriously affected the accuracy of QPI, which are frequently overlooked. When acquiring the original data, the sample being tested is habitually placed at the center of the field of view, unconsciously avoiding the influence of the boundary conditions, but this does not fundamentally solve the problem. When the size of the object being tested exceeds that of the imaging field of view (FOV), the boundary conditions cannot be avoided, and serious boundary artifacts will appear in the reconstructed FOV. In various QPI techniques, such as the transport of intensity equation (TIE), differential phase contrast (DPC), and Fourier ptychographic microscopy (FPM), it has been demonstrated that the boundary conditions can significantly impact the accuracy of the phase reconstruction. The most fundamental reason for the incorrect reconstruction results caused by the boundary conditions is the loss of information. This paper systematically studies the impact of the boundary conditions on the reconstruction accuracy of quantitative phase imaging and adaptive aberration correction based on FPM, and discusses the influence of data redundancy on boundary artifacts of phase reconstruction.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yao Jin, Yefeng Shu, Yuzhen Zhang, Jiasong Sun, and Chao Zuo "Impact of boundary conditions on accuracy of quantitative phase imaging", Proc. SPIE 12967, AOPC 2023: Computing Imaging Technology, 129670C (18 December 2023); https://doi.org/10.1117/12.3007991
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KEYWORDS
Boundary conditions

Phase reconstruction

Imaging systems

Image resolution

Phase imaging

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