scholarly journals Drift correction in localization microscopy using entropy minimization

2021 ◽  
Author(s):  
Jelmer Cnossen ◽  
Tao Ju Cui ◽  
Chirlmin Joo ◽  
Carlas S Smith
Keyword(s):  
Cross Correlation ◽  
Time Constraints ◽  
Fiducial Markers ◽  
Drift Correction ◽  
Localization Microscopy ◽  
Drift Estimation ◽  
Estimation Precision ◽  
2D And 3D ◽  
Dedicated Hardware ◽  
Compute Time

Localization microscopy offers resolutions down to a single nanometer, but currently requires additional dedicated hardware or fiducial markers to reduce resolution loss from drift of the sample. Drift estimation without fiducial markers is typically implemented using redundant cross correlation (RCC). We show that RCC has sub-optimal precision and bias, which leaves room for improvement. Here, we minimize a bound on the entropy of the obtained localizations to efficiently compute a precise drift estimate. Within practical compute-time constraints, simulations show a 5x improvement in drift estimation precision over the widely used RCC algorithm. The algorithm operates directly on fluorophore localizations and is tested on simulated and experimental datasets in 2D and 3D. An open source implementation is provided, implemented in Python and C++, and can utilize a GPU if available.

scholarly journals Localization events-based sample drift correction for localization microscopy with redundant cross-correlation algorithm

2014 ◽  
Vol 22 (13) ◽  
pp. 15982 ◽  
Author(s):  
Yina Wang ◽  
Joerg Schnitzbauer ◽  
Zhe Hu ◽  
Xueming Li ◽  
Yifan Cheng ◽  
...  
Keyword(s):  
Cross Correlation ◽  
Drift Correction ◽  
Localization Microscopy ◽  
Correlation Algorithm

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

Cross-correlation image tracking for drift correction and adsorbate analysis

2002 ◽  
Vol 73 (2) ◽  
pp. 313-317 ◽  
Author(s):  
B. A. Mantooth ◽  
Z. J. Donhauser ◽  
K. F. Kelly ◽  
P. S. Weiss
Keyword(s):  
Cross Correlation ◽  
Drift Correction ◽  
Image Tracking ◽  
Correlation Image

scholarly journals Sample drift correction in 3D fluorescence photoactivation localization microscopy

2011 ◽  
Vol 19 (16) ◽  
pp. 15009 ◽  
Author(s):  
Michael J. Mlodzianoski ◽  
John M. Schreiner ◽  
Steven P. Callahan ◽  
Katarina Smolková ◽  
Andrea Dlasková ◽  
...  
Keyword(s):  
Drift Correction ◽  
Localization Microscopy

scholarly journals X-Ray Cross-Correlation Analysis of Disordered Ensembles of Particles: Potentials and Limitations

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
R. P. Kurta ◽  
M. Altarelli ◽  
I. A. Vartanyants
Keyword(s):  
Correlation Analysis ◽  
Disordered Systems ◽  
Cross Correlation ◽  
Structural Information ◽  
Three Dimensional ◽  
X Ray ◽  
X Ray Scattering ◽  
Cross Correlation Analysis ◽  
2D And 3D ◽  
Ray Scattering

Angular X-ray cross-correlation analysis (XCCA) is an approach to study the structure of disordered systems using the results of X-ray scattering experiments. In this paper we summarize recent theoretical developments related to the Fourier analysis of the cross-correlation functions. Results of our simulations demonstrate the application of XCCA to two- and three-dimensional (2D and 3D) disordered ensembles of particles. We show that the structure of a single particle can be recovered using X-ray data collected from a 2D disordered system of identical particles. We also demonstrate that valuable structural information about the local structure of 3D systems, inaccessible from a standard small-angle X-ray scattering experiment, can be resolved using XCCA.

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 Drift correction in localization microscopy using entropy minimization

2021 ◽  
Author(s):  
Carlas Smith ◽  
chirlmin joo ◽  
jelmer Cnossen ◽  
Tao Ju Cui
Keyword(s):  
Drift Correction ◽  
Localization Microscopy ◽  
Entropy Minimization

scholarly journals Efficient Cross-Correlation Filtering of One- and Two-Color Single Molecule Localization Microscopy Data

2021 ◽  
Vol 1 ◽  
Author(s):  
Angel Mancebo ◽  
Dushyant Mehra ◽  
Chiranjib Banerjee ◽  
Do-Hyung Kim ◽  
Elias M. Puchner
Keyword(s):  
Single Molecule ◽  
Cross Correlation ◽  
Pair Correlation ◽  
Diffraction Limit ◽  
Optical Diffraction ◽  
Data Sets ◽  
Oligomeric State ◽  
Localization Microscopy ◽  
Cross Correlation Analysis ◽  
Single Molecule Localization Microscopy

Single molecule localization microscopy has become a prominent technique to quantitatively study biological processes below the optical diffraction limit. By fitting the intensity profile of single sparsely activated fluorophores, which are often attached to a specific biomolecule within a cell, the locations of all imaged fluorophores are obtained with ∼20 nm resolution in the form of a coordinate table. While rendered super-resolution images reveal structural features of intracellular structures below the optical diffraction limit, the ability to further analyze the molecular coordinates presents opportunities to gain additional quantitative insights into the spatial distribution of a biomolecule of interest. For instance, pair-correlation or radial distribution functions are employed as a measure of clustering, and cross-correlation analysis reveals the colocalization of two biomolecules in two-color SMLM data. Here, we present an efficient filtering method for SMLM data sets based on pair- or cross-correlation to isolate localizations that are clustered or appear in proximity to a second set of localizations in two-color SMLM data. In this way, clustered or colocalized localizations can be separately rendered and analyzed to compare other molecular properties to the remaining localizations, such as their oligomeric state or mobility in live cell experiments. Current matrix-based cross-correlation analyses of large data sets quickly reach the limitations of computer memory due to the space complexity of constructing the distance matrices. Our approach leverages k-dimensional trees to efficiently perform range searches, which dramatically reduces memory needs and the time for the analysis. We demonstrate the versatile applications of this method with simulated data sets as well as examples of two-color SMLM data. The provided MATLAB code and its description can be integrated into existing localization analysis packages and provides a useful resource to analyze SMLM data with new detail.

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