scholarly journals Analyzing Single Molecule Localization Microscopy Data Using Cubic Splines

2016 ◽  
Author(s):  
Hazen P. Babcock ◽  
Xiaowei Zhuang
Keyword(s):  
Single Molecule ◽  
Super Resolution ◽  
Computation Time ◽  
Cubic Splines ◽  
Localization Algorithm ◽  
Localization Microscopy ◽  
Analytical Functions ◽  
Open Source Software Package ◽  
Microscopy Data ◽  
Single Molecule Localization Microscopy

AbstractThe resolution of super-resolution microscopy based on single molecule localization is in part determined by the accuracy of the localization algorithm. In most published approaches to date this localization is done by fitting an analytical function that approximates the point spread function (PSF) of the microscope. However, particularly for localization in 3D, analytical functions such as a Gaussian, which are computationally inexpensive, may not accurately capture the PSF shape leading to reduced fitting accuracy. On the other hand, analytical functions that can accurately capture the PSF shape, such as those based on pupil functions, can be computationally expensive. Here we investigate the use of cubic splines as an alternative fitting approach. We demonstrate that cubic splines can capture the shape of any PSF with high accuracy and that they can be used for fitting the PSF with only a 2-3x increase in computation time as compared to Gaussian fitting. We provide an open-source software package that measures the PSF of any microscope and uses the measured PSF to perform 3D single molecule localization microscopy analysis with reasonable accuracy and speed.

A literature review of localization methods and emergence of deep learning in single-molecule localization microscopy

2020 ◽  
Author(s):  
Anish Mukherjee
Keyword(s):  
Deep Learning ◽  
Single Molecule ◽  
Super Resolution ◽  
Point Sources ◽  
Learning Approaches ◽  
Localization Algorithm ◽  
Localization Microscopy ◽  
Trade Offs ◽  
Emitter Localization ◽  
Single Molecule Localization Microscopy

The quality of super-resolution images largely depends on the performance of the emitter localization algorithm used to localize point sources. In this article, an overview of the various techniques which are used to localize point sources in single-molecule localization microscopy are discussed and their performances are compared. This overview can help readers to select a localization technique for their application. Also, an overview is presented about the emergence of deep learning methods that are becoming popular in various stages of single-molecule localization microscopy. The state of the art deep learning approaches are compared to the traditional approaches and the trade-offs of selecting an algorithm for localization are discussed.

scholarly journals ShareLoc – an open platform for sharing localization microscopy data

2021 ◽  
Author(s):  
Jiachuan Bai ◽  
Wei Ouyang ◽  
Manish Kumar Singh ◽  
Christophe Leterrier ◽  
Paul Barthelemy ◽  
...  
Keyword(s):  
Single Molecule ◽  
Super Resolution ◽  
Data Sets ◽  
Localization Microscopy ◽  
Open Platform ◽  
Machine Learning Methods ◽  
Microscopy Data ◽  
Analytical Tools ◽  
Existing Data ◽  
Single Molecule Localization Microscopy

Novel insights and more powerful analytical tools can emerge from the reanalysis of existing data sets, especially via machine learning methods. Despite the widespread use of single molecule localization microscopy (SMLM) for super-resolution bioimaging, the underlying data are often not publicly accessible. We developed ShareLoc (https://shareloc.xyz), an open platform designed to enable sharing, easy visualization and reanalysis of SMLM data. We discuss its features and show how data sharing can improve the performance and robustness of SMLM image reconstruction by deep learning.

scholarly journals Parameter-free rendering of single-molecule localization microscopy data for parameter-free resolution estimation

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Adrien C. Descloux ◽  
Kristin S. Grußmayer ◽  
Aleksandra Radenovic
Keyword(s):  
Single Molecule ◽  
Super Resolution ◽  
Free Resolution ◽  
Temporal Separation ◽  
Localization Microscopy ◽  
Resolution Imaging ◽  
Localization Precision ◽  
Microscopy Data ◽  
Resolution Estimation ◽  
Single Molecule Localization Microscopy

AbstractLocalization microscopy is a super-resolution imaging technique that relies on the spatial and temporal separation of blinking fluorescent emitters. These blinking events can be individually localized with a precision significantly smaller than the classical diffraction limit. This sub-diffraction localization precision is theoretically bounded by the number of photons emitted per molecule and by the sensor noise. These parameters can be estimated from the raw images. Alternatively, the resolution can be estimated from a rendered image of the localizations. Here, we show how the rendering of localization datasets can influence the resolution estimation based on decorrelation analysis. We demonstrate that a modified histogram rendering, termed bilinear histogram, circumvents the biases introduced by Gaussian or standard histogram rendering. We propose a parameter-free processing pipeline and show that the resolution estimation becomes a function of the localization density and the localization precision, on both simulated and state-of-the-art experimental datasets.

scholarly journals Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software

2019 ◽  
Vol 16 (5) ◽  
pp. 387-395 ◽  
Author(s):  
Daniel Sage ◽  
Thanh-An Pham ◽  
Hazen Babcock ◽  
Tomas Lukes ◽  
Thomas Pengo ◽  
...  
Keyword(s):  
Single Molecule ◽  
Super Resolution ◽  
Localization Microscopy ◽  
Fight Club ◽  
2D And 3D ◽  
Single Molecule Localization Microscopy

scholarly journals SMoLR: visualization and analysis of single-molecule localization microscopy data in R

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Maarten W. Paul ◽  
H. Martijn de Gruiter ◽  
Zhanmin Lin ◽  
Willy M. Baarends ◽  
Wiggert A. van Cappellen ◽  
...  
Keyword(s):  
Single Molecule ◽  
Localization Microscopy ◽  
Microscopy Data ◽  
Single Molecule Localization Microscopy

scholarly journals Super-resolution fight club: A broad assessment of 2D & 3D single-molecule localization microscopy software

2018 ◽  
Author(s):  
Daniel Sage ◽  
Thanh-An Pham ◽  
Hazen Babcock ◽  
Tomas Lukes ◽  
Thomas Pengo ◽  
...  
Keyword(s):  
Single Molecule ◽  
Double Helix ◽  
Super Resolution ◽  
Large Set ◽  
Holistic View ◽  
Localization Microscopy ◽  
Fight Club ◽  
Community Effort ◽  
2D And 3D ◽  
Single Molecule Localization Microscopy

ABSTRACTWith the widespread uptake of 2D and 3D single molecule localization microscopy, a large set of different data analysis packages have been developed to generate super-resolution images. To guide researchers on the optimal analytical software for their experiments, we have designed, in a large community effort, a competition to extensively characterise and rank these options. We generated realistic simulated datasets for popular imaging modalities – 2D, astigmatic 3D, biplane 3D, and double helix 3D – and evaluated 36 participant packages against these data. This provides the first broad assessment of 3D single molecule localization microscopy software, provides a holistic view of how the latest 2D and 3D single molecule localization software perform in realistic conditions, and ultimately provides insight into the current limits of the field.

scholarly journals Molecular resolution imaging by post-labeling expansion single-molecule localization microscopy (Ex-SMLM)

2020 ◽  
Author(s):  
Fabian U. Zwettler ◽  
Sebastian Reinhard ◽  
Davide Gambarotto ◽  
Toby D. M. Bell ◽  
Virginie Hamel ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Single Molecule ◽  
Super Resolution ◽  
Reference Structure ◽  
Positional Error ◽  
Localization Microscopy ◽  
Resolution Imaging ◽  
Endogenous Proteins ◽  
Super Resolution Microscopy ◽  
Single Molecule Localization Microscopy

AbstractExpansion microscopy (ExM) enables super-resolution fluorescence imaging of physically expanded biological samples with conventional microscopes. By combining expansion microscopy (ExM) with single-molecule localization microscopy (SMLM) it is potentially possible to approach the resolution of electron microscopy. However, current attempts to combine both methods remained challenging because of protein and fluorophore loss during digestion or denaturation, gelation, and the incompatibility of expanded polyelectrolyte hydrogels with photoswitching buffers. Here we show that re-embedding of expanded hydrogels enables dSTORM imaging of expanded samples and demonstrate that post-labeling ExM resolves the current limitations of super-resolution microscopy. Using microtubules as a reference structure and centrioles, we demonstrate that post-labeling Ex-SMLM preserves ultrastructural details, improves the labeling efficiency and reduces the positional error arising from linking fluorophores into the gel thus paving the way for super-resolution imaging of immunolabeled endogenous proteins with true molecular resolution.

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