scholarly journals Lensless Three-Dimensional Quantitative Phase Imaging Using Phase Retrieval Algorithm

2020 ◽  
Vol 6 (9) ◽  
pp. 99 ◽  
Author(s):  
Vijayakumar Anand ◽  
Tomas Katkus ◽  
Denver P. Linklater ◽  
Elena P. Ivanova ◽  
Saulius Juodkazis
Keyword(s):  
Phase Retrieval ◽  
Three Dimensional ◽  
Retrieval Algorithm ◽  
Phase Imaging ◽  
Label Free ◽  
Quantitative Phase Imaging ◽  
Single Plane ◽  
Quantitative Phase ◽  
Web Camera ◽  
Phase Retrieval Algorithm

Quantitative phase imaging (QPI) techniques are widely used for the label-free examining of transparent biological samples. QPI techniques can be broadly classified into interference-based and interferenceless methods. The interferometric methods which record the complex amplitude are usually bulky with many optical components and use coherent illumination. The interferenceless approaches which need only the intensity distribution and works using phase retrieval algorithms have gained attention as they require lesser resources, cost, space and can work with incoherent illumination. With rapid developments in computational optical techniques and deep learning, QPI has reached new levels of applications. In this tutorial, we discuss one of the basic optical configurations of a lensless QPI technique based on the phase-retrieval algorithm. Simulative studies on QPI of thin, thick, and greyscale phase objects with assistive pseudo-codes and computational codes in Octave is provided. Binary phase samples with positive and negative resist profiles were fabricated using lithography, and a single plane and two plane phase objects were constructed. Light diffracted from a point object is modulated by phase samples and the corresponding intensity patterns are recorded. The phase retrieval approach is applied for 2D and 3D phase reconstructions. Commented codes in Octave for image acquisition and automation using a web camera in an open source operating system are provided.

scholarly journals Multi-ATOM: Ultrahigh-throughput single-cell quantitative phase imaging with subcellular resolution

2019 ◽  
Author(s):  
Kelvin C. M. Lee ◽  
Andy K. S. Lau ◽  
Anson H. L. Tang ◽  
Maolin Wang ◽  
Aaron T. Y. Mok ◽  
...  
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Large Scale ◽  
Phase Retrieval ◽  
Leukemic Cells ◽  
Phase Imaging ◽  
Label Free ◽  
Quantitative Phase Imaging ◽  
Phase Gradient ◽  
Quantitative Phase

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.

scholarly journals Measuring three-dimensional dynamics of platelet activation using 3-D quantitative phase imaging

2019 ◽  
Author(s):  
SangYun Lee ◽  
Seongsoo Jang ◽  
YongKeun Park
Keyword(s):  
Platelet Activation ◽  
Three Dimensional ◽  
Dry Mass ◽  
Phase Imaging ◽  
Label Free ◽  
Quantitative Phase Imaging ◽  
Biochemical Alterations ◽  
Quantitative Phase ◽  
Before And After ◽  
Quantitative Manner

AbstractPlatelets, or thrombocytes, are anucleated tiny blood cells with an indispensable contribution to the hemostatic properties of whole blood, detecting injured sites at the surface of blood vessels and forming blood clots. Here, we quantitatively and non-invasively investigated the morphological and biochemical alterations of individual platelets during activation in the absence of exogenous agents by employing 3-D quantitative phase imaging (QPI). By reconstructing 3-D refractive index (RI) tomograms of individual platelets, we investigated alterations in platelet activation before and after the administration of various platelet agonists. Our results showed that while the integrity of collagen-stimulated platelets was preserved despite the existence of a few degranulated platelets with developed pseudopods, platelets stimulated by thrombin or thrombin receptor-activating peptide (TRAP) exhibited significantly lower cellular concentration and dry mass than did resting platelets. Our work provides a means to systematically investigate drug-respondents of individual platelets in a label-free and quantitative manner, and open a new avenue to the study of the activation of platelets.Abstract Figure

scholarly journals Rapid and label-free identification of individual bacterial pathogens exploiting three-dimensional quantitative phase imaging and deep learning

2019 ◽  
Author(s):  
Geon Kim ◽  
Daewoong Ahn ◽  
Minhee Kang ◽  
YoungJu Jo ◽  
Donghun Ryu ◽  
...  
Keyword(s):  
Refractive Index ◽  
Deep Learning ◽  
Infectious Diseases ◽  
Bacterial Pathogens ◽  
Bacterial Species ◽  
Three Dimensional ◽  
Phase Imaging ◽  
Label Free ◽  
Quantitative Phase Imaging ◽  
Quantitative Phase

ABSTRACTFor appropriate treatments of infectious diseases, rapid identification of the pathogens is crucial. Here, we developed a rapid and label-free method for identifying common bacterial pathogens as individual bacteria by using three-dimensional quantitative phase imaging and deep learning. We achieved 95% accuracy in classifying 19 bacterial species by exploiting the rich information in three-dimensional refractive index tomograms with a convolutional neural network classifier. Extensive analysis of the features extracted by the trained classifier was carried out, which supported that our classifier is capable of learning species-dependent characteristics. We also confirmed that utilizing three-dimensional refractive index tomograms was crucial for identification ability compared to two-dimensional imaging. This method, which does not require time-consuming culture, shows high feasibility for diagnosing patients with infectious diseases who would benefit from immediate and adequate antibiotic treatment.

3D morphological and biophysical changes in a single tachyzoite and its infected cells using three‐dimensional quantitative phase imaging

2020 ◽  
Vol 13 (8) ◽  
Author(s):  
Egy Rahman Firdaus ◽  
Ji‐Hoon Park ◽  
Seong‐Kyun Lee ◽  
YongKeun Park ◽  
Guang‐Ho Cha ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Phase Imaging ◽  
Quantitative Phase Imaging ◽  
Quantitative Phase ◽  
Infected Cells ◽  
Biophysical Changes

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 ◽  
...  
Keyword(s):  
Phase Retrieval ◽  
Imaging Techniques ◽  
Phase Imaging ◽  
Quantitative Phase Imaging ◽  
Temperature Drift ◽  
Retrieval Method ◽  
Computing Power ◽  
Quantitative Phase ◽  
Air Turbulence ◽  
Tissue Discrimination

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.

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