scholarly journals Enhanced super-resolution microscopy by extreme value based emitter recovery

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hongqiang Ma ◽  
Wei Jiang ◽  
Jianquan Xu ◽  
Yang Liu
Keyword(s):  
Super Resolution ◽  
Extreme Value ◽  
Biological Structure ◽  
Manual Adjustment ◽  
Imaging Characteristics ◽  
Nanoscale Imaging ◽  
Super Resolution Microscopy ◽  
Adjustment Of Parameters ◽  
Imagej Plugin

AbstractSuper-resolution localization microscopy allows visualization of biological structure at nanoscale resolution. However, the presence of heterogeneous background can degrade the nanoscale resolution by tens of nanometers and introduce significant image artifacts. Here we investigate and validate an efficient approach, referred to as extreme value-based emitter recovery (EVER), to accurately recover the distorted fluorescent emitters from heterogeneous background. Through numerical simulation and biological experiments, we validated the accuracy of EVER in improving the fidelity of the reconstructed super-resolution image for a wide variety of imaging characteristics. EVER requires no manual adjustment of parameters and has been implemented as an easy-to-use ImageJ plugin that can immediately enhance the quality of reconstructed super-resolution images. This method is validated as an efficient way for robust nanoscale imaging of samples with heterogeneous background fluorescence, such as thicker tissue and cells.

scholarly journals Enhanced super-resolution microscopy by extreme value based emitter recovery

2018 ◽  
Author(s):  
Hongqiang Ma ◽  
Wei Jiang ◽  
Jianquan Xu ◽  
Yang Liu
Keyword(s):  
Super Resolution ◽  
Extreme Value ◽  
New Approach ◽  
Manual Adjustment ◽  
Imaging Characteristics ◽  
Nanoscale Imaging ◽  
Super Resolution Microscopy ◽  
Adjustment Of Parameters ◽  
Imagej Plugin

ABSTRACTSuper-resolution localization microscopy allows visualization of biological structure at nanoscale resolution. However, the presence of heterogeneous background can degrade the nanoscale resolution by tens of nanometers and introduce significant image artifacts. Here we develop a new approach, referred to as extreme value based emitter recovery (EVER), to accurately recover the distorted fluorescent emitters from heterogeneous background. Through numerical simulation and biological experiments, we demonstrate that EVER significantly improves the accuracy and fidelity of the reconstructed super-resolution image for a wide variety of imaging characteristics. EVER requires no manual adjustment of parameters and is implemented as an easy-to-use ImageJ plugin that can immediately enhance the quality of super-resolution images. Our method paves the way for accurate nanoscale imaging of samples with heterogeneous background fluorescence, such as thicker tissue and cells.

scholarly journals Corrected Super-Resolution Microscopy Enables Nanoscale Imaging of Autofluorescent Lung Macrophages

2020 ◽  
Vol 119 (12) ◽  
pp. 2403-2417
Author(s):  
Ashley R. Ambrose ◽  
Susanne Dechantsreiter ◽  
Rajesh Shah ◽  
M. Angeles Montero ◽  
Anne Marie Quinn ◽  
...  
Keyword(s):  
Super Resolution ◽  
Lung Macrophages ◽  
Nanoscale Imaging ◽  
Super Resolution Microscopy

scholarly journals A Method for Quantifying Molecular Interactions Using Stochastic Modelling and Super-Resolution Microscopy

2017 ◽  
Author(s):  
Keria Bermudez-Hernandez ◽  
Sarah Keegan ◽  
Donna R. Whelan ◽  
Dylan A. Reid ◽  
Jennifer Zagelbaum ◽  
...  
Keyword(s):  
Super Resolution ◽  
Stochastic Modelling ◽  
Analytical Form ◽  
Molecular Clusters ◽  
Interaction Factor ◽  
Cluster Density ◽  
Super Resolution Microscopy ◽  
The Relationship ◽  
Microscopy Images ◽  
Imagej Plugin

AbstractWe introduce the Interaction Factor (IF), a measure for quantifying the interaction of molecular clusters in super-resolution microscopy images. The IF is robust in the sense that it is independent of cluster density, and it only depends on the extent of the pair-wise interaction between different types of molecular clusters in the image. The IF for a single or a collection of images is estimated by first using stochastic modelling where the locations of clusters in the images are repeatedly randomized to estimate the distribution of the overlaps between the clusters in the absence of interaction (IF=0). Second, an analytical form of the relationship between IF and the overlap (which has the random overlap as its only parameter) is used to estimate the IF for the experimentally observed overlap. The advantage of IF compared to conventional methods to quantify interaction in microscopy images is that it is insensitive to changing cluster density and is an absolute measure of interaction, making the interpretation of experiments easier. We validate the IF method by using both simulated and experimental data and provide an ImageJ plugin for determining the IF of an image.

scholarly journals SpineJ : A software tool for quantitative analysis of nanoscale spine morphology

2019 ◽  
Author(s):  
Florian Levet ◽  
Jan Tønnesen ◽  
Valentin Nägerl ◽  
Jean-Baptiste Sibarita
Keyword(s):  
Super Resolution ◽  
Software Tool ◽  
Neuronal Function ◽  
Spine Morphology ◽  
Nanoscale Structures ◽  
Structural Details ◽  
User Friendly ◽  
Super Resolution Microscopy ◽  
Friendly Graphical User Interface ◽  
Imagej Plugin

AbstractSuper-resolution microscopy provides diffraction-unlimited optical access to the intricate morphology of neurons in living brain tissue, resolving their finest structural details, which are critical for neuronal function. However, as existing image analysis software tools have been developed for diffraction-limited images, they are generally not well suited for quantifying nanoscale structures like dendritic spines. We present SpineJ, a semi-automatic ImageJ plugin that is specifically designed for this purpose. SpineJ comes with an intuitive and user-friendly graphical user interface, facilitating fast, accurate, and unbiased analysis of spine morphology.

The power in your pocket – uncover smartphones for use as cutting-edge microscopic instruments in science and research

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Haoran Wang ◽  
Rainer Heintzmann ◽  
Benedict Diederich
Keyword(s):  
Sea Water ◽  
Point Of Care ◽  
Super Resolution ◽  
Handheld Devices ◽  
Microscopy Imaging ◽  
Complex Functions ◽  
Computer Based ◽  
3D Printed ◽  
Super Resolution Microscopy

Abstract Since the development of the first light microscope over 400 years ago, the technology has continuously evolved and established itself as a powerful tool, especially in biology, diagnostics and point-of-care (PoC) applications. The miniaturization of mass-produced actuators and sensors enables the use of technically extremely complex functions in smartphones at a very low price. They can be used to implement modern microscopy methods for use in places where access to such techniques is often very limited. In this review, we show how easy it is to integrate a smartphone into the everyday microscopy-imaging routines of biology research. Such devices have also been used to identify diseases directly at the patient. Furthermore, we demonstrate how constantly increasing computing power in combination with the steadily improving imaging quality of cameras of handheld devices enables the realization of new biomedical imaging methods, which together with commercially available and 3D-printed components make current research available to a broad mass. Examples are smartphone-based super-resolution microscopy (SRM) or task-specific single-board computer-based devices, which can analyze plankton in sea water.

scholarly journals Effect of labeling density and time post labeling on quality of antibody-based super resolution microscopy images

2015 ◽  
Author(s):  
Amy M. Bittel ◽  
Isaac Saldivar ◽  
Nicholas Dolman ◽  
Andrew K. Nickerson ◽  
Li-Jung Lin ◽  
...  
Keyword(s):  
Super Resolution ◽  
Super Resolution Microscopy ◽  
Microscopy Images

Super-Resolution Microscopy in Studying the Structure and Function of the Cell Nucleus

Acta Naturae ◽  
2017 ◽  
Vol 9 (4) ◽  
pp. 42-51
Author(s):  
S. S. Ryabichko ◽  
◽  
A. N. Ibragimov ◽  
L. A. Lebedeva ◽  
E. N. Kozlov ◽  
...  
Keyword(s):  
Cell Nucleus ◽  
Super Resolution ◽  
Structure And Function ◽  
And Function ◽  
Super Resolution Microscopy
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