scholarly journals Variable Wavefront Curvature Phase Retrieval Compared to Off-Axis Holography and Its Useful Application to Support Intraoperative Tissue Discrimination

2018 ◽  
Vol 8 (11) ◽  
pp. 2147 ◽  
Author(s):  
Daniel Claus ◽  
Jörg Hennenlotter ◽  
Qi Liting ◽  
Giancarlo Pedrini ◽  
Arnulf Stenzl ◽  
...  

Quantitative phase imaging can reveal morphological features without having to stain the biological sample. This property has important implications for intraoperative applications since the time spent during histopathology can be reduced from a few minutes to a few seconds. However, most common quantitative phase imaging techniques are based on the interferometric principle, which makes them more prone to disturbing environmental influences, such as temperature drift and air turbulence. In the last decade, with the advance of computing power, many different iterative quantitative phase imaging techniques, which only require the recording of the diffracted wavefield, and therefore offer increased robustness towards environmental disturbances, have been proposed. These are particularly well-suited for the application outside the well-controlled lab environment such as an operating theatre. The optical performance of our developed iterative phase retrieval method based on variable wavefront curvature will be evaluated by reference to off-axis digital holography and applied for intraoperative discrimination of tissue.

Sensors ◽  
2013 ◽  
Vol 13 (4) ◽  
pp. 4170-4191 ◽  
Author(s):  
KyeoReh Lee ◽  
Kyoohyun Kim ◽  
Jaehwang Jung ◽  
JiHan Heo ◽  
Sangyeon Cho ◽  
...  

Author(s):  
Marco Antonio Sandoval Hernández ◽  
Noel-Ivan Toto-Arellano ◽  
L. A. Bonilla Jiménez ◽  
J. A. Martínez Domínguez ◽  
Luis García Lechuga ◽  
...  

2017 ◽  
Author(s):  
GwangSik Park ◽  
Dongsik Han ◽  
GwangSu Kim ◽  
Seungwoo Shin ◽  
Kyoohyun Kim ◽  
...  

Microfluidic mixing plays a key role in various fields, including biomedicine and chemical engineering. To date, although various approaches for imaging microfluidic mixing have been proposed, they provide only quantitative imaging capability and require for exogenous labeling agents. Quantitative phase imaging techniques, however, circumvent these problems and offer label-free quantitative information about concentration maps of microfluidic mixing. We present the quantitative phase imaging of microfluidic mixing in various types of PDMS microfluidic channels with different geometries; the feasibility of the present method was validated by comparing it with the results obtained by theoretical calculation based on Fick’s law.


2019 ◽  
Author(s):  
Kelvin C. M. Lee ◽  
Andy K. S. Lau ◽  
Anson H. L. Tang ◽  
Maolin Wang ◽  
Aaron T. Y. Mok ◽  
...  

AbstractA growing body of evidence has substantiated the significance of quantitative phase imaging (QPI) in enabling cost-effective and label-free cellular assay, which provides useful insights into understanding biophysical properties of cells and their roles in cellular functions. However, available QPI modalities are limited by the loss of imaging resolution at high throughput and thus run short of sufficient statistical power at the single cell precision to define cell identities in a large and heterogeneous population of cells – hindering their utility in mainstream biomedicine and biology. Here we present a new QPI modality, coined multi-ATOM that captures and processes quantitative label-free single-cell images at ultra-high throughput without compromising sub-cellular resolution. We show that multi-ATOM, based upon ultrafast phase-gradient encoding, outperforms state-of-the-art QPI in permitting robust phase retrieval at a QPI throughput of >10,000 cell/sec, bypassing the need for interferometry which inevitably compromises QPI quality under ultrafast operation. We employ multi-ATOM for large-scale, label-free, multi-variate, cell-type classification (e.g. breast cancer sub-types, and leukemic cells versus peripheral blood mononuclear cells) at high accuracy (>94%). Our results suggest that multi-ATOM could empower new strategies in large-scale biophysical single-cell analysis with applications in biology and enriching disease diagnostics.


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