scholarly journals Topography and refractometry of sperm cells using SLIM

2017 ◽  
Author(s):  
Lina Liu ◽  
Mikhail E. Kandel ◽  
Marcello Rubessa ◽  
Sierra Schreiber ◽  
Mathew Wheeler ◽  
...  
Keyword(s):  
Refractive Index ◽  
Interference Microscopy ◽  
Phase Imaging ◽  
Label Free ◽  
Quantitative Phase Imaging ◽  
Ensemble Averaging ◽  
Thickness Profile ◽  
Light Interference ◽  
Phase Sensitive

AbstractCharacterization of spermatozoon viability is a common test in treating infertility. Recently, it has been shown that label-free, phase-sensitive imaging can provide a valuable alternative for this type of assay. Here, we employ spatial light interference microscopy (SLIM) to decouple the thickness and refractive index information of individual cells. This procedure was enabled by quantitative phase imaging cells on media of two different refractive indices and using a numerical tool to remove the curvature from the cell tails. This way, we achieved ensemble averaging of topography and refractometry of 100 cells in each of the two groups. The results show that the thickness profile of the cell tail goes down to 150 nm and the refractive index can reach values of 1.6 close to the head.

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.

scholarly journals Epi-illumination gradient light interference microscopy for imaging opaque structures

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Mikhail E. Kandel ◽  
Chenfei Hu ◽  
Ghazal Naseri Kouzehgarani ◽  
Eunjung Min ◽  
Kathryn Michele Sullivan ◽  
...  
Keyword(s):  
Multiple Scattering ◽  
Imaging Modality ◽  
Single Cells ◽  
Scattering Problem ◽  
Biological Tissues ◽  
Interference Microscopy ◽  
Model Organisms ◽  
Phase Imaging ◽  
Label Free ◽  
Light Interference

Abstract Multiple scattering and absorption limit the depth at which biological tissues can be imaged with light. In thick unlabeled specimens, multiple scattering randomizes the phase of the field and absorption attenuates light that travels long optical paths. These obstacles limit the performance of transmission imaging. To mitigate these challenges, we developed an epi-illumination gradient light interference microscope (epi-GLIM) as a label-free phase imaging modality applicable to bulk or opaque samples. Epi-GLIM enables studying turbid structures that are hundreds of microns thick and otherwise opaque to transmitted light. We demonstrate this approach with a variety of man-made and biological samples that are incompatible with imaging in a transmission geometry: semiconductors wafers, specimens on opaque and birefringent substrates, cells in microplates, and bulk tissues. We demonstrate that the epi-GLIM data can be used to solve the inverse scattering problem and reconstruct the tomography of single cells and model organisms.

scholarly journals Monitoring Reactivation of Latent HIV by Label-Free Gradient Light Interference Microscopy

iScience ◽  
2021 ◽  
pp. 102940
Author(s):  
Neha Goswami ◽  
Yiyang Lu ◽  
Mikhail E. Kandel ◽  
Michael J. Fanous ◽  
Kathrin Bohn-Wippert ◽  
...  
Keyword(s):  
Interference Microscopy ◽  
Label Free ◽  
Light Interference ◽  
Latent Hiv
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