Warning: Undefined array key "mm" in /www/wwwroot/www.ai-bt.com/si.php on line 10 Deprecated: trim(): Passing null to parameter #1 ($string) of type string is deprecated in /www/wwwroot/www.ai-bt.com/si.php on line 10 Theory and practical recommendations for autocorrelation-based image correlation spectroscopy.

Literature DB >> 23224160

Theory and practical recommendations for autocorrelation-based image correlation spectroscopy.

Abstract

Image correlation spectroscopy (ICS) is a powerful technique for detecting arrangement of fluorophores in images. This tutorial gives background into the mathematical underpinnings of ICS, specifically image autocorrelation. The effects of various artifacts and image processing steps, including background subtraction, noise, and image morphology were examined analytically and their effects on ICS analysis modeled. A series of recommendations was built based on this analysis.

Mesh：

Year: 2012 PMID： 23224160 PMCID： PMC3414238 DOI： 10.1117/1.JBO.17.8.080801

Source DB: PubMed Journal: J Biomed Opt ISSN： 1083-3668 Impact factor: 3.170

23 in total

1. Counting dendritic spines in brain tissue slices by image correlation spectroscopy analysis.

Authors: P W Wiseman; F Capani; J A Squier; M E Martone
Journal: J Microsc Date: 2002-02 Impact factor: 1.758

2. Spatiotemporal image correlation spectroscopy (STICS) theory, verification, and application to protein velocity mapping in living CHO cells.

Authors: Benedict Hebert; Santiago Costantino; Paul W Wiseman
Journal: Biophys J Date: 2005-02-18 Impact factor: 4.033

3. Accuracy and dynamic range of spatial image correlation and cross-correlation spectroscopy.

Authors: Santiago Costantino; Jonathan W D Comeau; David L Kolin; Paul W Wiseman
Journal: Biophys J Date: 2005-05-27 Impact factor: 4.033

4. Image correlation spectroscopy.

Authors: Anja Nohe; Nils O Petersen
Journal: Sci STKE Date: 2007-12-18

5. Image correlation spectroscopy of multiphoton images correlates with collagen mechanical properties.

Authors: Christopher B Raub; Jay Unruh; Vinod Suresh; Tatiana Krasieva; Tore Lindmo; Enrico Gratton; Bruce J Tromberg; Steven C George
Journal: Biophys J Date: 2007-12-07 Impact factor: 4.033

6. Measuring diffusion of lipid-like probes in artificial and natural membranes by raster image correlation spectroscopy (RICS): use of a commercial laser-scanning microscope with analog detection.

Authors: Ellen Gielen; Nick Smisdom; Martin vandeVen; Ben De Clercq; Enrico Gratton; Michelle Digman; Jean-Michel Rigo; Johan Hofkens; Yves Engelborghs; Marcel Ameloot
Journal: Langmuir Date: 2009-05-05 Impact factor: 3.882

7. Quantification of biological interactions with particle image cross-correlation spectroscopy (PICCS).

Authors: Stefan Semrau; Laurent Holtzer; Marcos González-Gaitán; Thomas Schmidt
Journal: Biophys J Date: 2011-04-06 Impact factor: 4.033

8. Quantitation of membrane receptor distributions by image correlation spectroscopy: concept and application.

Authors: N O Petersen; P L Höddelius; P W Wiseman; O Seger; K E Magnusson
Journal: Biophys J Date: 1993-09 Impact factor: 4.033

9. Oxidative stress increases angiotensin receptor type I responsiveness by increasing receptor degree of aggregation using image correlation spectroscopy.

Authors: Titiwat Sungkaworn; Yongwimon Lenbury; Varanuj Chatsudthipong
Journal: Biochim Biophys Acta Date: 2011-07-23

10. The efficacy of image correlation spectroscopy for characterization of the extracellular matrix.

Authors: Sadiq Mohammed Mir; Brenda Baggett; Urs Utzinger
Journal: Biomed Opt Express Date: 2012-01-03 Impact factor: 3.732

11 in total

1. Confocal Microscopy Reveals Cell Surface Receptor Aggregation Through Image Correlation Spectroscopy.

Authors: Adam C Parslow; Andrew H A Clayton; Peter Lock; Andrew M Scott
Journal: J Vis Exp Date: 2018-08-02 Impact factor: 1.355

2. Optical imaging predicts mechanical properties during decellularization of cardiac tissue.

Authors: Nick Merna; Claire Robertson; Anh La; Steven C George
Journal: Tissue Eng Part C Methods Date: 2013-05-01 Impact factor: 3.056

3. The microstructure of laminin-111 compensates for dystroglycan loss in mammary epithelial cells in downstream expression of milk proteins.

Authors: A J Kent; N Mayer; J L Inman; C Hochman-Mendez; M J Bissell; C Robertson
Journal: Biomaterials Date: 2019-07-09 Impact factor: 12.479

4. Motor-Driven Restructuring of Cytoskeleton Composites Leads to Tunable Time-Varying Elasticity.

Authors: Janet Y Sheung; Daisy H Achiriloaie; Christopher Currie; Karthik Peddireddy; Aaron Xie; Jessalyn Simon-Parker; Gloria Lee; Michael J Rust; Moumita Das; Jennifer L Ross; Rae M Robertson-Anderson
Journal: ACS Macro Lett Date: 2021-09-03 Impact factor: 7.015

5. Active cytoskeletal composites display emergent tunable contractility and restructuring.

Authors: Gloria Lee; Gregor Leech; Pancy Lwin; Jonathan Michel; Christopher Currie; Michael J Rust; Jennifer L Ross; Ryan J McGorty; Moumita Das; Rae M Robertson-Anderson
Journal: Soft Matter Date: 2021-12-08 Impact factor: 4.046

6. Multiscale analysis of collagen microstructure with generalized image correlation spectroscopy and the detection of tissue prestress.

Authors: Claire Robertson; Kenji Ikemura; Tatiana B Krasieva; Steven C George
Journal: Biomaterials Date: 2013-05-03 Impact factor: 12.479