@inproceedings{0abf36248a0842489abe56c49bb0e902,
title = "Unlabeled flow cellular deformation measurement based on digital holographic microscopy",
abstract = "Living cells as phase objects require not only non-invasive measurement but also quantitative phase information during dynamic biopsy. Digital Holographic Microscopy (DHM), measuring three-dimensional morphology without changing the active condition of cells and in situ inspection, is becoming excellent tools for biology research. We have described a DHM method for quantitative, unlabeled observation of living cell subjected to fluid shear stress (FSS) in flowing fluid. The holographic recording system combined with the fluid shear system is improved. The numerical reconstruction technique firstly employed deep learning Convolutional Neural Network model filter, which achieved automatically processing large scale the spectrum of holograms immediately. Osteocytes as the experimental samples were observed and their morphological changes under the stimulation of FSS was successfully measured.",
keywords = "Convolutional Neural Network, Digital Holographic Microscopy, Dynamic biopsy, Fluid Shear Stress, Frequency Filtering, Living cells measurement, U-Net",
author = "Wen Xiao and Qixiang Wang and Feng Pan and Runyu Cao and Xiaosu Yi",
note = "Publisher Copyright: {\textcopyright} 2018 SPIE.; Interferometry XIX 2018 ; Conference date: 21-08-2018 Through 23-08-2018",
year = "2018",
doi = "10.1117/12.2324852",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Katherine Creath and Jan Burke and Davies, \{Angela D.\} and \{North Morris\}, \{Michael B.\} and Katherine Creath",
booktitle = "Interferometry XIX",
address = "美国",
}