TY - JOUR
T1 - Quantitative Phase Imaging Using Deep Learning-Based Holographic Microscope
AU - Di, Jianglei
AU - Wu, Ji
AU - Wang, Kaiqiang
AU - Tang, Ju
AU - Li, Ying
AU - Zhao, Jianlin
N1 - Publisher Copyright:
© Copyright © 2021 Di, Wu, Wang, Tang, Li and Zhao.
PY - 2021/3/22
Y1 - 2021/3/22
N2 - Digital holographic microscopy enables the measurement of the quantitative light field information and the visualization of transparent specimens. It can be implemented for complex amplitude imaging and thus for the investigation of biological samples including tissues, dry mass, membrane fluctuation, etc. Currently, deep learning technologies are developing rapidly and have already been applied to various important tasks in the coherent imaging. In this paper, an optimized structural convolution neural network PhaseNet is proposed for the reconstruction of digital holograms, and a deep learning-based holographic microscope using above neural network is implemented for quantitative phase imaging. Living mouse osteoblastic cells are quantitatively measured to demonstrate the capability and applicability of the system.
AB - Digital holographic microscopy enables the measurement of the quantitative light field information and the visualization of transparent specimens. It can be implemented for complex amplitude imaging and thus for the investigation of biological samples including tissues, dry mass, membrane fluctuation, etc. Currently, deep learning technologies are developing rapidly and have already been applied to various important tasks in the coherent imaging. In this paper, an optimized structural convolution neural network PhaseNet is proposed for the reconstruction of digital holograms, and a deep learning-based holographic microscope using above neural network is implemented for quantitative phase imaging. Living mouse osteoblastic cells are quantitatively measured to demonstrate the capability and applicability of the system.
KW - convolution neural network
KW - deep learning
KW - digital holographic microscopy
KW - digital holography
KW - quantitative phase imaging
UR - http://www.scopus.com/inward/record.url?scp=85103615578&partnerID=8YFLogxK
U2 - 10.3389/fphy.2021.651313
DO - 10.3389/fphy.2021.651313
M3 - 文章
AN - SCOPUS:85103615578
SN - 2296-424X
VL - 9
JO - Frontiers in Physics
JF - Frontiers in Physics
M1 - 651313
ER -