Deep-Learning-Based Halo-Free White-Light Diffraction Phase Imaging

被引:3
|
作者
Zhang, Kehua [1 ]
Zhu, Miaomiao [1 ]
Ma, Lihong [2 ,3 ]
Zhang, Jiaheng [2 ,3 ]
Li, Yong [2 ,3 ]
机构
[1] Zhejiang Normal Univ, Key Lab Urban Rail Transit Intelligent Operat & M, Jinhua, Zhejiang, Peoples R China
[2] Zhejiang Normal Univ, Inst Informat Opt, Jinhua, Zhejiang, Peoples R China
[3] Zhejiang Normal Univ, Key Lab Opt Informat Detecting & Display Technol, Jinhua, Zhejiang, Peoples R China
基金
中国国家自然科学基金;
关键词
quantitative phase imaging; diffraction phase microscopy; deep learning; halo-free; white-light illumination; DIGITAL HOLOGRAPHIC MICROSCOPY; CONTRAST MICROSCOPY; COHERENCE; RECONSTRUCTION; COMPENSATION; ARCHITECTURE; REDUCTION; FIELD;
D O I
10.3389/fphy.2021.650108
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
In white-light diffraction phase imaging, when used with insufficient spatial filtering, phase image exhibits object-dependent artifacts, especially around the edges of the object, referred to the well-known halo effect. Here we present a new deep-learning-based approach for recovering halo-free white-light diffraction phase images. The neural network-based method can accurately and rapidly remove the halo artifacts not relying on any priori knowledge. First, the neural network, namely HFDNN (deep neural network for halo free), is designed. Then, the HFDNN is trained by using pairs of the measured phase images, acquired by white-light diffraction phase imaging system, and the true phase images. After the training, the HFDNN takes a measured phase image as input to rapidly correct the halo artifacts and reconstruct an accurate halo-free phase image. We validate the effectiveness and the robustness of the method by correcting the phase images on various samples, including standard polystyrene beads, living red blood cells and monascus spores and hyphaes. In contrast to the existing halo-free methods, the proposed HFDNN method does not rely on the hardware design or does not need iterative computations, providing a new avenue to all halo-free white-light phase imaging techniques.
引用
收藏
页数:11
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