Journal articles: 'Image Correlation Spectroscopy'

1

Nohe, A., and N. O. Petersen. "Image Correlation Spectroscopy." Science's STKE 2007, no. 417 (December 11, 2007): pl7. http://dx.doi.org/10.1126/stke.4172007pl7.

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Wiseman, P. W., J. A. Squier, M. H. Ellisman, and K. R. Wilson. "Two-photon image correlation spectroscopy and image cross-correlation spectroscopy." Journal of Microscopy 200, no. 1 (October 2000): 14–25. http://dx.doi.org/10.1046/j.1365-2818.2000.00736.x.

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3

Digman, Michelle A., and Enrico Gratton. "Scanning image correlation spectroscopy." BioEssays 34, no. 5 (March 13, 2012): 377–85. http://dx.doi.org/10.1002/bies.201100118.

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4

Kurniawan, Nicholas A., and Raj Rajagopalan. "Probe-Independent Image Correlation Spectroscopy." Langmuir 27, no. 6 (March 15, 2011): 2775–82. http://dx.doi.org/10.1021/la104478x.

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5

Hendrix, Jelle, Tomas Dekens, and Don C. Lamb. "Arbitrary-Region Image Correlation Spectroscopy." Biophysical Journal 110, no. 3 (February 2016): 176a. http://dx.doi.org/10.1016/j.bpj.2015.11.983.

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6

Wiseman, Paul W. "Image Correlation Spectroscopy: Principles and Applications." Cold Spring Harbor Protocols 2015, no. 4 (April 2015): pdb.top086124. http://dx.doi.org/10.1101/pdb.top086124.

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7

Hendrix, Jelle, Tomas Dekens, Waldemar Schrimpf, and Don C. Lamb. "Arbitrary-Region Raster Image Correlation Spectroscopy." Biophysical Journal 111, no. 8 (October 2016): 1785–96. http://dx.doi.org/10.1016/j.bpj.2016.09.012.

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Semrau, Stefan, Laurent Holtzer, Marcos Gonzalez-Gaitan, and Thomas Schmidt. "Particle Image Cross Correlation Spectroscopy (PICCS)." Biophysical Journal 98, no. 3 (January 2010): 182a. http://dx.doi.org/10.1016/j.bpj.2009.12.976.

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Longfils, Marco, Nick Smisdom, Marcel Ameloot, Mats Rudemo, Veerle Lemmens, Guillermo Solís Fernández, Magnus Röding, Niklas Lorén, Jelle Hendrix, and Aila Särkkä. "Raster Image Correlation Spectroscopy Performance Evaluation." Biophysical Journal 117, no. 10 (November 2019): 1900–1914. http://dx.doi.org/10.1016/j.bpj.2019.09.045.

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10

Rossow, Molly J., Jennifer M. Sasaki, Michelle A. Digman, and Enrico Gratton. "Raster image correlation spectroscopy in live cells." Nature Protocols 5, no. 11 (October 14, 2010): 1761–74. http://dx.doi.org/10.1038/nprot.2010.122.

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11

Wiseman, Paul. "Introduction to Fluorescence and Image Correlation Spectroscopy." Microscopy and Microanalysis 10, S02 (August 2004): 246–47. http://dx.doi.org/10.1017/s1431927604886483.

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12

Spendier, Kathrin, and James L. Thomas. "Image correlation spectroscopy of randomly distributed disks." Journal of Biological Physics 37, no. 4 (August 18, 2011): 477–92. http://dx.doi.org/10.1007/s10867-011-9232-x.

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13

Raub, Christopher B., Jay Unruh, Vinod Suresh, Tatiana Krasieva, Tore Lindmo, Enrico Gratton, Bruce J. Tromberg, and Steven C. George. "Image Correlation Spectroscopy of Multiphoton Images Correlates with Collagen Mechanical Properties." Biophysical Journal 94, no. 6 (March 2008): 2361–73. http://dx.doi.org/10.1529/biophysj.107.120006.

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14

Srivastava, M., N. O. Petersen, G. R. Mount, D. M. Kingston, and N. S. McIntyre. "Analysis of three-dimensional SIMS images using image cross-correlation spectroscopy." Surface and Interface Analysis 26, no. 3 (March 1998): 188–94. http://dx.doi.org/10.1002/(sici)1096-9918(199803)26:3<188::aid-sia359>3.0.co;2-e.

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15

Kang, Kyongok. "Mesoscopic relaxation time of dynamic image correlation spectroscopy." Journal of Biomedical Science and Engineering 03, no. 06 (2010): 625–32. http://dx.doi.org/10.4236/jbise.2010.36085.

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16

Costantino, Santiago, Jonathan W. D. Comeau, David L. Kolin, and Paul W. Wiseman. "Accuracy and Dynamic Range of Spatial Image Correlation and Cross-Correlation Spectroscopy." Biophysical Journal 89, no. 2 (August 2005): 1251–60. http://dx.doi.org/10.1529/biophysj.104.057364.

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Prummer, Michael, Sannah Zoffmann, Vanessa Klug, and Dorothee Kling. "A Cell Motility Assay Based on Image Correlation Spectroscopy." Biophysical Journal 102, no. 3 (January 2012): 191a—192a. http://dx.doi.org/10.1016/j.bpj.2011.11.1046.

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18

Nohe, Anja, Eleonora Keating, Crystal Loh, Michael T. Underhill, and Nils O. Petersen. "Caveolin-1 isoform reorganization studied by image correlation spectroscopy." Faraday Discussions 126 (2004): 185. http://dx.doi.org/10.1039/b304943d.

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Prummer, Michael, Dorothee Kling, Vanessa Trefzer, Thilo Enderle, Sannah Zoffmann, and Marco Prunotto. "A Random Motility Assay Based on Image Correlation Spectroscopy." Biophysical Journal 104, no. 11 (June 2013): 2362–72. http://dx.doi.org/10.1016/j.bpj.2013.04.031.

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20

Tanner, Kandice, Donald Ferris, Luca Lanzano, Berhan Mandefro, William W. Mantulin, David Gardiner, Elizabeth Rugg, and Enrico Gratton. "Image Correlation Spectroscopy Reveals Global Dynamics of Wound Healing." Biophysical Journal 96, no. 3 (February 2009): 42a. http://dx.doi.org/10.1016/j.bpj.2008.12.114.

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21

Civita, Simone, Ranieri Bizzarri, Paolo Bianchini, and Alberto Diaspro. "Image correlation spectroscopy approaches to probe diffusion in cell." Biophysical Journal 122, no. 3 (February 2023): 274a. http://dx.doi.org/10.1016/j.bpj.2022.11.1563.

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22

Nieves, D. J., Y. Li, D. G. Fernig, and R. Lévy. "Photothermal raster image correlation spectroscopy of gold nanoparticles in solution and on live cells." Royal Society Open Science 2, no. 6 (June 2015): 140454. http://dx.doi.org/10.1098/rsos.140454.

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Raster image correlation spectroscopy (RICS) measures the diffusion of fluorescently labelled molecules from stacks of confocal microscopy images by analysing correlations within the image. RICS enables the observation of a greater and, thus, more representative area of a biological system as compared to other single molecule approaches. Photothermal microscopy of gold nanoparticles allows long-term imaging of the same labelled molecules without photobleaching. Here, we implement RICS analysis on a photothermal microscope. The imaging of single gold nanoparticles at pixel dwell times short enough for RICS (60 μs) with a piezo-driven photothermal heterodyne microscope is demonstrated (photothermal raster image correlation spectroscopy, PhRICS). As a proof of principle, PhRICS is used to measure the diffusion coefficient of gold nanoparticles in glycerol : water solutions. The diffusion coefficients of the nanoparticles measured by PhRICS are consistent with their size, determined by transmission electron microscopy. PhRICS was then used to probe the diffusion speed of gold nanoparticle-labelled fibroblast growth factor 2 (FGF2) bound to heparan sulfate in the pericellular matrix of live fibroblast cells. The data are consistent with previous single nanoparticle tracking studies of the diffusion of FGF2 on these cells. Importantly, the data reveal faster FGF2 movement, previously inaccessible by photothermal tracking, and suggest that inhomogeneity in the distribution of bound FGF2 is dynamic.

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23

Brewer, Jonathan, Maria Bloksgaard, Jakub Kubiak, and Luis Bagatolli. "Fluorescent Correlation Spectroscopy and Raster Image Correlation Spectroscopy as a Tool to Measure Diffusion in the Human Epidermis." Biophysical Journal 100, no. 3 (February 2011): 630a. http://dx.doi.org/10.1016/j.bpj.2010.12.3623.

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24

Benn, A. G., and R. J. Kulperger. "Integrated marked Poisson processes with application to image correlation spectroscopy." Canadian Journal of Statistics 25, no. 2 (June 1997): 215–31. http://dx.doi.org/10.2307/3315733.

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25

Kolin, David L., Santiago Costantino, and Paul W. Wiseman. "Sampling Effects, Noise, and Photobleaching in Temporal Image Correlation Spectroscopy." Biophysical Journal 90, no. 2 (January 2006): 628–39. http://dx.doi.org/10.1529/biophysj.105.072322.

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26

Kitamura, Akira, Hiroki Shimizu, and Masataka Kinjo. "Determination of cytoplasmic optineurin foci sizes using image correlation spectroscopy." Journal of Biochemistry 164, no. 3 (April 19, 2018): 223–29. http://dx.doi.org/10.1093/jb/mvy044.

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27

DE METS, R., A. DELON, M. BALLAND, O. DESTAING, and I. WANG. "Dynamic range and background filtering in raster image correlation spectroscopy." Journal of Microscopy 279, no. 2 (June 8, 2020): 123–38. http://dx.doi.org/10.1111/jmi.12925.

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28

Rowland, David J., Hannah H. Tuson, and Julie S. Biteen. "Resolving Fast, Confined Diffusion in Bacteria with Image Correlation Spectroscopy." Biophysical Journal 110, no. 10 (May 2016): 2241–51. http://dx.doi.org/10.1016/j.bpj.2016.04.023.

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29

Ciccotosto, Giuseppe D., Noga Kozer, Timothy T. Y. Chow, James W. M. Chon, and Andrew H. A. Clayton. "Aggregation Distributions on Cells Determined by Photobleaching Image Correlation Spectroscopy." Biophysical Journal 104, no. 5 (March 2013): 1056–64. http://dx.doi.org/10.1016/j.bpj.2013.01.009.

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30

Robertson, Claire. "Theory and practical recommendations for autocorrelation-based image correlation spectroscopy." Journal of Biomedical Optics 17, no. 8 (August 8, 2012): 080801. http://dx.doi.org/10.1117/1.jbo.17.8.080801.

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31

Chushkin, Y., C. Caronna, and A. Madsen. "A novel event correlation scheme for X-ray photon correlation spectroscopy." Journal of Applied Crystallography 45, no. 4 (June 20, 2012): 807–13. http://dx.doi.org/10.1107/s0021889812023321.

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X-ray photon correlation spectroscopy (XPCS) was employed to measure the time-dependent intermediate scattering function in an organic molecular glass former. Slow translational dynamics were probed in the glassy state and the correlation functions were calculated from two-dimensional speckle patterns recorded by a CCD detector. The image frames were analysed using a droplet algorithm together with an event correlation scheme. This method provides results analogous to standard intensity correlation algorithms but is much faster, hence addressing the recurrent problem of insufficient computing power for online analysis in XPCS. The event correlator has a wide range of potential future applications at synchrotrons and free-electron laser sources.

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32

Rossow, Molly, William W. Mantulin, and Enrico Gratton. "Spatiotemporal image correlation spectroscopy measurements of flow demonstrated in microfluidic channels." Journal of Biomedical Optics 14, no. 2 (2009): 024014. http://dx.doi.org/10.1117/1.3088203.

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33

Gröner, Nadine, Jérémie Capoulade, Christoph Cremer, and Malte Wachsmuth. "Measuring and imaging diffusion with multiple scan speed image correlation spectroscopy." Optics Express 18, no. 20 (September 22, 2010): 21225. http://dx.doi.org/10.1364/oe.18.021225.

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34

Kurniawan, Nicholas Agung, Chwee Teck Lim, and Raj Rajagopalan. "Image correlation spectroscopy as a tool for microrheology of soft materials." Soft Matter 6, no. 15 (2010): 3499. http://dx.doi.org/10.1039/c002265a.

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35

Semrau, Stefan, Piet Lommerse, Margot Beukers, and Thomas Schmidt. "Adenosine A1 Receptor Signaling Unraveled By Particle Image Correlation Spectroscopy (PICS)." Biophysical Journal 96, no. 3 (February 2009): 368a. http://dx.doi.org/10.1016/j.bpj.2008.12.1983.

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36

Semrau, Stefan, Laurent Holtzer, Marcos González-Gaitán, and Thomas Schmidt. "Quantification of Biological Interactions with Particle Image Cross-Correlation Spectroscopy (PICCS)." Biophysical Journal 100, no. 7 (April 2011): 1810–18. http://dx.doi.org/10.1016/j.bpj.2010.12.3746.

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37

Wiseman, Paul W. "Advances in Image Correlation Spectroscopy for Measurements in Heterogeneous Cell Environments." Biophysical Journal 102, no. 3 (January 2012): 6a. http://dx.doi.org/10.1016/j.bpj.2011.11.050.

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38

Kulkarni, R. P., D. D. Wu, M. E. Davis, and S. E. Fraser. "Quantitating intracellular transport of polyplexes by spatio-temporal image correlation spectroscopy." Proceedings of the National Academy of Sciences 102, no. 21 (May 16, 2005): 7523–28. http://dx.doi.org/10.1073/pnas.0501950102.

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39

IMMERSTRAND, CHARLOTTE, JOEL HEDLUND, KARL–ERIC MAGNUSSON, TOMMY SUNDQVIST, and KAJSA HOLMGREN PETERSON. "Organelle transport in melanophores analyzed by white light image correlation spectroscopy." Journal of Microscopy 225, no. 3 (March 2007): 275–82. http://dx.doi.org/10.1111/j.1365-2818.2007.01743.x.

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40

Rocheleau, Jonathan V., and Nils O. Petersen. "The Sendai virus membrane fusion mechanism studied using image correlation spectroscopy." European Journal of Biochemistry 268, no. 10 (May 15, 2001): 2924–30. http://dx.doi.org/10.1046/j.1432-1327.2001.02181.x.

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41

Danaf, Nader. "Image Correlation Spectroscopy based Assay to Investigate G-Protein Coupled Receptors." Biophysical Journal 112, no. 3 (February 2017): 146a. http://dx.doi.org/10.1016/j.bpj.2016.11.803.

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42

Staley, Ben, Egor Zindy, and Alain Pluen. "Quantifying uptake and distribution of arginine rich peptides at therapeutic concentrations using fluorescence correlation spectroscopy and image correlation spectroscopy techniques." Drug Discovery Today 15, no. 23-24 (December 2010): 1099. http://dx.doi.org/10.1016/j.drudis.2010.09.402.

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43

Cainero, Isotta, Elena Cerutti, Mario Faretta, Gaetano Ivan Dellino, Pier Giuseppe Pelicci, Alberto Diaspro, and Luca Lanzanò. "Measuring Nanoscale Distances by Structured Illumination Microscopy and Image Cross-Correlation Spectroscopy (SIM-ICCS)." Sensors 21, no. 6 (March 12, 2021): 2010. http://dx.doi.org/10.3390/s21062010.

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Since the introduction of super-resolution microscopy, there has been growing interest in quantifying the nanoscale spatial distributions of fluorescent probes to better understand cellular processes and their interactions. One way to check if distributions are correlated or not is to perform colocalization analysis of multi-color acquisitions. Among all the possible methods available to study and quantify the colocalization between multicolor images, there is image cross-correlation spectroscopy (ICCS). The main advantage of ICCS, in comparison with other co-localization techniques, is that it does not require pre-segmentation of the sample into single objects. Here we show that the combination of structured illumination microscopy (SIM) with ICCS (SIM-ICCS) is a simple approach to quantify colocalization and measure nanoscale distances from multi-color SIM images. We validate the SIM-ICCS analysis on SIM images of optical nanorulers, DNA-origami-based model samples containing fluorophores of different colors at a distance of 80 nm. The SIM-ICCS analysis is compared with an object-based analysis performed on the same samples. Finally, we show that SIM-ICCS can be used to quantify the nanoscale spatial distribution of functional nuclear sites in fixed cells.

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44

Liu, Fulong, Gang Li, Shuqiang Yang, Wenjuan Yan, Guoquan He, and Ling Lin. "Recognition of Heterogeneous Edges in Multiwavelength Transmission Images Based on the Weighted Constraint Decision Method." Applied Spectroscopy 74, no. 8 (June 10, 2020): 883–93. http://dx.doi.org/10.1177/0003702820908951.

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Multiwavelength light transmission imaging provides a possibility for early detection of breast cancer. However, due to strong scattering during the transmission process of breast tissue analysis, the transmitted image signal is weak and the image is blurred and this makes heterogeneous edge detection difficult. This paper proposes a method based on the weighted constraint decision (WCD) method to eliminate the erosion and checkerboard effects in image histogram equalization (HE) enhancement and to improve the recognition of heterogeneous edge. Multiwavelength transmission images of phantom are acquired on the designed experimental system and the mask image with high signal-to-noise ratio (SNR) is obtained by frame accumulation and an Otsu thresholding model. Then, during image enhancement the image is divided into low-gray-level (LGL) and high-gray-level (HGL) regions according to the distribution of light intensity in image. And the probability density distribution of gray level in the LGL and HGL regions are redefined respectively according to the WCD method. Finally, the reconstructed image is obtained based on the modified HE. The experimental results show that compared with traditional image enhancement methods, the WCD method proposed in this paper can greatly improve the contrast between heterogeneous region and normal region. Moreover, the correlation between the original image data is maintained to the greatest extent, so that the edge of the heterogeneity can be detected more accurately. In conclusion, the WCD method not only accurately identifies the edge of heterogeneity in multiwavelength transmission images, but it also could improve the clinical application of multiwavelength transmission images in the early detection of breast cancer.

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45

Semrau, S., and T. Schmidt. "Particle Image Correlation Spectroscopy (PICS): Retrieving Nanometer-Scale Correlations from High-Density Single-Molecule Position Data." Biophysical Journal 92, no. 2 (January 2007): 613–21. http://dx.doi.org/10.1529/biophysj.106.092577.

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46

Bachir, Alexia I., Nela Durisic, Benedict Hebert, Peter Grütter, and Paul W. Wiseman. "Characterization of blinking dynamics in quantum dot ensembles using image correlation spectroscopy." Journal of Applied Physics 99, no. 6 (March 15, 2006): 064503. http://dx.doi.org/10.1063/1.2175470.

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47

Mir, Sadiq Mohammed, Brenda Baggett, and Urs Utzinger. "The efficacy of image correlation spectroscopy for characterization of the extracellular matrix." Biomedical Optics Express 3, no. 2 (January 3, 2012): 215. http://dx.doi.org/10.1364/boe.3.000215.

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48

Coppola, S., G. Caracciolo, and T. Schmidt. "Exact occupation probabilities for intermittent transport and application to image correlation spectroscopy." New Journal of Physics 16, no. 11 (November 24, 2014): 113057. http://dx.doi.org/10.1088/1367-2630/16/11/113057.

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49

Wiseman, P. W., F. Capani, J. A. Squier, and M. E. Martone. "Counting dendritic spines in brain tissue slices by image correlation spectroscopy analysis." Journal of Microscopy 205, no. 2 (February 2002): 177–86. http://dx.doi.org/10.1046/j.0022-2720.2001.00985.x.

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50

Petersen, N. O., P. L. Höddelius, P. W. Wiseman, O. Seger, and K. E. Magnusson. "Quantitation of membrane receptor distributions by image correlation spectroscopy: concept and application." Biophysical Journal 65, no. 3 (September 1993): 1135–46. http://dx.doi.org/10.1016/s0006-3495(93)81173-1.

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Journal articles on the topic 'Image Correlation Spectroscopy'

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