|
Real-time GPU-based 3D Deconvolution |
Optics Express, Vol. 21, Issue 4, pp. 4766-4773 (2013)
http://dx.doi.org/10.1364/OE.21.004766
Enhanced HTML 
Acrobat PDF (1542 KB)
Abstract
Confocal microscopy is an oft-used technique in biology. Deconvolution of 3D images reduces blurring from out-of-focus light and enables quantitative analyses, but existing software for deconvolution is slow and expensive. We present a parallelized software method that runs within ImageJ and deconvolves 3D images ~100 times faster than conventional software (few seconds per image) by running on a low-cost graphics processor board (GPU). We demonstrate the utility of this software by analyzing microclusters of T cell receptors in the immunological synapse of a CD4 + T cell and dendritic cell. This software provides a low-cost and rapid way to improve the accuracy of 3D microscopic images obtained by any method.
© 2013 OSA
OCIS Codes
(100.1830) Image processing : Deconvolution
(180.2520) Microscopy : Fluorescence microscopy
ToC Category:
Image Processing
History
Original Manuscript: December 17, 2012
Revised Manuscript: January 21, 2013
Manuscript Accepted: January 31, 2013
Published: February 19, 2013
Virtual Issues
Vol. 8, Iss. 3 Virtual Journal for Biomedical Optics
Citation
Marc A. Bruce and Manish J. Butte, "Real-time GPU-based 3D Deconvolution," Opt. Express 21, 4766-4773 (2013)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-21-4-4766
Sort: Year | Journal | Reset
References
- F. Sedarat, E. Lin, E. D. W. Moore, and G. F. Tibbits, “Deconvolution of confocal images of dihydropyridine and ryanodine receptors in developing cardiomyocytes,” J. Appl. Physiol.97(3), 1098–1103 (2004). [CrossRef] [PubMed]
- B. Storrie, T. Starr, and K. Forsten-Williams, “Using quantitative fluorescence microscopy to probe organelle assembly and membrane trafficking,” Methods Mol. Biol.457, 179–192 (2008). [CrossRef] [PubMed]
- K. Mehta, A. D. Hoppe, R. Kainkaryam, P. J. Woolf, and J. J. Linderman, “A computational approach to inferring cellular protein-binding affinities from quantitative fluorescence resonance energy transfer imaging,” Proteomics9(23), 5371–5383 (2009). [CrossRef] [PubMed]
- A. Edelstein, N. Amodaj, K. Hoover, R. Vale, and N. Stuurman, Computer Control of Microscopes Using µManager, Current Protocols in Molecular Biology (John Wiley & Sons, Inc., 2010).
- J. Hoberock and N. Bell, “Thrust: A Parallel Template Library,” (2010), retrieved http://www.meganewtons.com/ .
- J. B. Pawley, Handbook of Biological Confocal Microscopy (Kluwer Academic Publishers, 1995).
- J. B. Sibarita, “Deconvolution microscopy,” Microscopy Techniques, 1288–1291 (2005).
- Y. Hiraoka, J. W. Sedat, and D. A. Agard, “Determination of three-dimensional imaging properties of a light microscope system. Partial confocal behavior in epifluorescence microscopy,” Biophys. J.57(2), 325–333 (1990). [CrossRef] [PubMed]
- J. G. McNally, T. Karpova, J. Cooper, and J. A. Conchello, “Three-dimensional imaging by deconvolution microscopy,” Methods19(3), 373–385 (1999). [CrossRef] [PubMed]
- R. P. Dougherty, “Diffraction PSF 3D,” (2005), retrieved http://www.optinav.com/Diffraction-PSF-3D.htm .
- L. Lucy, “An iterative technique for the rectification of observed distributions,” Astron. J.79, 745 (1974). [CrossRef]
- W. Richardson, “Bayesian-based iterative method of image reconstruction,” J. Opt. Soc. Am.62(1), 55–59 (1972). [CrossRef]
- D. S. Biggs, “3D Deconvolution Microscopy,” in Current Protocols in Cytometry (Wiley Online Library, 2010), Chap. 12, Unit 12 19, pp. 11–20.
- A. Griffa, N. Garin, and D. Sage, “Hollow Bars,” retrieved http://bigwww.epfl.ch/deconvolution/?p=bars .
- A. Griffa, N. Garin, and D. Sage, “C. elegans embryo” retrieved http://bigwww.epfl.ch/deconvolution/?p=bio .
- S. C. Bunnell, D. I. Hong, J. R. Kardon, T. Yamazaki, C. J. McGlade, V. A. Barr, and L. E. Samelson, “T cell receptor ligation induces the formation of dynamically regulated signaling assemblies,” J. Cell Biol.158(7), 1263–1275 (2002). [CrossRef] [PubMed]
- P. J. Lu, P. A. Sims, H. Oki, J. B. Macarthur, and D. A. Weitz, “Target-locking acquisition with real-time confocal (TARC) microscopy,” Opt. Express15(14), 8702–8712 (2007). [CrossRef] [PubMed]
Cited By |
 Alert me when this paper is cited |
OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.
Related Journal Articles 
- Coherent use of opposing lenses for axial resolution increase. II. Power and limitation of nonlinear image restoration (JOSAA)
- Coherent use of opposing lenses for axial resolution increase in fluorescence microscopy. I. Comparative study of concepts (JOSAA)
- 4Pi microscopy deconvolution with a variable point-spread function (AO)
- Automatic deconvolution in 4Pi-microscopy with variable phase (OE)
- Removal of subsurface fluorescence in cryo-imaging using deconvolution (OE)
Related Conference Papers
- Fluorescence 3D-microscopy with 100 nm resolution
- Long Exposure Point Spread Function Estimation from Adaptive Optics Loop Data
- The Application of Deconvolution to Adaptive Optics Retinal Images
- Block-Processing Method for Post-Detection Correction of Anisoplanatic Adaptive Optics Images
- The Application of Deconvolution to Adaptive Optics Retinal Images
« Previous Article | Next Article »
OSA is a member of 