QSIM: quantitative structured illumination microscopy image processing in ImageJ

BioMedical Engineering OnLine

Liang Gao¹ 

[1] Department of Biomedical Engineering, Washington University, St. Louis, MO 63139, USA

关键词: ImageJ;    3D imaging;    Quantitative imaging;    Structured illumination microscopy;   

Others  :  1097891
DOI  :  10.1186/1475-925X-14-4

 received in 2014-10-16, accepted in 2015-01-07,  发布年份 2015

【 摘 要 】

Background

Structured illumination microscopy has been extensively used in biological imaging due to its low cost and easy implementation. However, the lack of quantitative imaging capability limits its application in absolute irradiance measurements.

Method

We have developed a quantitative structured illumination microscopy image processing algorithm (QSIM) as a plugin for the widely used ImageJ software. QSIM can work with the raw images acquired by a traditional structured illumination microscope and can quantitatively measure photon numbers, with noise estimates for both wide-field images and sectioned images.

Results and conclusion

We demonstrated the quantitative image processing capability of QSIM by imaging a mouse kidney section in 3D. The results show that QSIM can transform structured illumination microscopy from qualitative to quantitative, which is essential for demanding fluorescence imaging applications.

【 授权许可】

   
2015 Gao; licensee BioMed Central.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

【 参考文献 】

• [1]Neil MAA, Juskaitis R, Wilson T: Method of obtaining optical sectioning by using structured light in a conventional microscope. Opt Lett 1997, 22:1905.
• [2]Karadaglic D, Wilson T: Image formation in structured illumination wide-field fluorescence microscopy. Micron 2008, 39:808-18.
• [3]Le Couteur DG, Cogger VC, McNerney GP, Nyunt T, DeLeve LD, et al.: Three-dimensional structured illumination microscopy of liver sinusoidal endothelial cell fenestrations. J Struct Biol 2010, 171:382-8.
• [4]Cremer C, Best G, Amberger R, Baddeley D, Ach T, et al.: Structured illumination microscopy of autofluorescent aggregations in human tissue. Micron 2011, 42:330-5.
• [5]Smalley MJ, Signoret N, Robertson D, Tilley A, Hann A, et al.: Dishevelled (Dvl-2) activates canonical Wnt signalling in the absence of cytoplasmic puncta. J Cell Sci 2005, 118:5279-89.
• [6]Ohlstein B, Spradling A: The adult Drosophila posterior midgut is maintained by pluripotent stem cells. Nature 2006, 439:470-4.
• [7]Sheppard CJR, Gan X, Gu M, Roy M: Signal-to-noise in confocal microscopes. In Handbook of biological confocal microscopy. Edited by Pawley JB. New York, NY: Springer; 2006.
• [8]Murray JM, Appleton PL, Swedlow JR, Waters JC: Evaluating performance in three-dimensional fluorescence microscopy. J Microsc-Oxford 2007, 228:390-405.
• [9]Waters JC: Accuracy and precision in quantitative fluorescence microscopy. J Cell Biol 2009, 185:1135-48.
• [10]Hagen N, Gao L, Tkaczyk TS: Quantitative sectioning and noise analysis for structured illumination microscopy. Opt Express 2012, 20:403-13.
• [11]Pietraszewska-Bogiel A, Gadella T: FRET microscopy: from principle to routine technology in cell biology. J Microsc 2010, 241:111-8.
• [12]Haustein E, Schwille P: Fluorescence correlation spectroscopy: novel variations of an established technique. Annu Rev Biophys Biomol Struct 2007, 36:151-69.
• [13]Diamond KR, Farrell TJ, Patterson MS: Measurement of fluorophore concentrations and fluorescence quantum yield in tissue-simulating phantoms using three diffusion models of steady-state spatially resolved fluorescence. Phys Med Biol 2003, 48:4135-49.