Abstract
The spatial resolution of chemical images acquired with cluster secondary ion mass spectrometry (SIMS) is limited not only by the size of the probe utilized to create the images but also by detection sensitivity. As the probe size is reduced to below 1 μm, for example, a low signal in each pixel limits lateral resolution because of counting statistics considerations. Although it can be useful to implement numerical methods to mitigate this problem, here we investigate the use of image fusion to combine information from scanning electron microscope (SEM) data with chemically resolved SIMS images. The advantage of this approach is that the higher intensity and, hence, spatial resolution of the electron images can help to improve the quality of the SIMS images without sacrificing chemical specificity. Using a pan-sharpening algorithm, the method is illustrated using synthetic data, experimental data acquired from a metallic grid sample, and experimental data acquired from a lawn of algae cells. The results show that up to an order of magnitude increase in spatial resolution is possible to achieve. A cross-correlation metric is utilized for evaluating the reliability of the procedure.
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Fletcher, J.S., Lockyer, N.P., Vickerman, J.C.: Molecular SIMS imaging; spatial resolution and molecular sensitivity: have we reached the end of the road? Is there light at the end of the tunnel? Surf. Interface Anal. 43, 253–256 (2011)
Piehowski, P.D., Davey, A.M., Kurczy, M.E., Sheets, E.D., Winograd, N., Ewing, A.G., Heien, M.L.: Time-of-flight secondary ion mass spectrometry imaging of subcellular lipid heterogeneity: Poisson counting and spatial resolution. Anal. Chem. 81, 5593–5602 (2009)
Henderson, A., Fletcher, J.S., Vickerman, J.C.: A comparison of PCA and MAF for ToF-SIMS image interpretation. Surf. Interface Anal. 41, 666–674 (2009)
Tyler, B.J., Rayal, G., Castner, D.G.: Multivariate analysis strategies for processing ToF-SIMS images of biomaterials. Biomaterials 28, 2412–2423 (2007)
Tyler, B.: Interpretation of TOF-SIMS images: multivariate and univariate approaches to image de-noising, image segmentation and compound identification. Appl. Surf. Sci. 203, 825–831 (2003)
Wickes, B.T., Kim, Y., Castner, D.G.: Denoising and multivariate analysis of time-of-flight SIMS images. Surf. Interface Anal. 35, 640–648 (2003)
Wang, Z., Zhou, D., Armenakis, C., Li, D., Li, Q.: A comparative analysis of image fusion methods. IEEE Trans. Geosci. Remote Sensing 43, 1391–1402 (2005)
Mumtaz, A., Majid, A., Mumtaz, A.: Genetic Algorithms and Its Application to Image Fusion. Proceedings of the International Conference on Emerging Technologies, Rawalpindi, Pakistan, October 18–19, 6–10 (2008)
Khan, A.M., Khan, A.: Fusion of visible and thermal images using support vector machines. Proceedings of the 10th IEEE International Multitopic Conference, Islamabad, Pakistan, December 23–24, 146–151 (2006)
Wen, C.Y., Chen, J.K.: Multi-resolution image fusion technique and its application to forensic science. Forensic Sci. Int. 140, 217–232 (2004)
Ashoori, A., Moshiri, B., Setarehdan, S.K.: Fuzzy image fusion application in detecting coronary layers in IVUS pictures. S.K. Proceedings of the 3rd International Symposium on Communications, Control, and Signal Processing, St. Julian's, Malta, March 12–14, Vols 1/3, 20–24 (2008)
Rubio-Guivernau, J.L., Gurchenkov, V., Luengo-Oroz, M.A., Duloquin, L., Bourgine, P., Santos, A., Peyrieras, N., Ledesma-Carbayo, M.J.: Wavelet-based image fusion in multi-view three-dimensional microscopy. Bioinformatics 28, 238–245 (2012)
Zhong, Z., Blum, R.S.: A categorization of multiscale-decomposition-based image fusion schemes with a performance study for a digital camera application. Proc. IEEE 87, 1315–1326 (1999)
Shivsubramani Krishnamoorthy, K.P.S.: Implemetation and comparative study of image fusion algorithms. Int. J. Comput. Appl. 9, 25–35 (2010)
Artyushkova, K., Pylypenko, S., Dowlapalli, M., Atanassov, P.: Use of digital image processing of microscopic images and multivariate analysis for quantitative correlation of morphology, activity, and durability of electrocatalysts. RSC Advances 2, 4304–4310 (2012)
Artyushkova, K., Fulghum, J.E.: Multivariate image analysis methods applied to XPS imaging data sets. Surf. Interface Anal. 33, 185–195 (2002)
Lloyd, K.G., Walls, D.J., Wyre, J.P.: Correlating data from multiple surface-specific techniques using multivariate methods: examples and considerations. Surf. Interface Anal. 41, 686–693 (2009)
Rokni, K., Marghany, M., Hashim, M., Hazini, S.: Comparative statistical-based and color-related pan sharpening algorithms for ASTER and RADARSAT SAR satellite data. IEEE International Conference on Computer Applications and Industrial Electronics (ICCAIE), Penang, Malaysia, December 4–7, 618–622 (2011)
Artyushkova, K., Farrar, J.O., Fulghum, J.E.: Data fusion of XPS and AFM images for chemical phase identification in polymer blends. Surf. Interface Anal. 41, 119–126 (2009)
Simpson, A.J., Zang, X., Kramer, R., Hatcher, P.G.: New insights on the structure of algaenan from Botryoccocus braunii race A and its hexane insoluble botryals based on multidimensional NMR spectroscopy and electrospray-mass spectrometry techniques. Phytochemistry 62, 783–796 (2003)
Tanoi, T., Kawachi, M., Watanabe, M.M.: Effects of carbon source on growth and morphology of Botryococcus braunii. J. Appl. Phycol. 23, 25–33 (2011)
Weiss, T.L., Chun, H.J., Okada, S., Vitha, S., Holzenburg, A., Laane, J., Devarenne, T.P.: Raman spectroscopy analysis of botryococcene hydrocarbons from the green microalga Botryococcus braunii. J. Biol. Chem. 285, 32458–32466 (2010)
Padwick, C., Pacifici, F., Smallwood, S.: WorldView-2 Pan-Sharpening. Proceedings of the ASPRS Annual Conference, San Diego, California, US, April 26–30 (2010)
Fletcher, J.S., Rabbani, S., Henderson, A., Blenkinsopp, P., Thompson, S.P., Lockyer, N.P., Vickerman, J.C.: A new dynamic in mass spectral imaging of single biological cells. Anal. Chem. 80, 9058–9064 (2008)
Pavlic, G., Singhroy, V., Duk-Rodkin, A., Alasset, P.J.: Satellite data fusion techniques for terrain and surficial geological mapping. Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE Int 3, 314 (2008)
Zitova, B., Flusser, J.: Image registration methods: a survey. Image Vision Comput 21, 977–1000 (2003)
Manjusha Deshmukh, U.B.: Image fusion and image quality assessment of fused images. Int. J. Image Processing 4, 484–508 (2010)
Weiss, T.L., Roth, R., Goodson, C., Vitha, S., Black, I., Azadi, P., Rusch, J., Holzenburg, A., Devarenne, T.P., Goodenough, U.: Colony organization in the green alga Botryococcus braunii (Race B) is specified by a complex extracellular matrix. Eukaryotic Cell 11, 1424–1440 (2012)
Oner, E.T.: Pretreatment Techniques for Biofuels and Biorefineries; Springer, Berlin, pp. 35–36 (2013)
Acknowledgments
The authors acknowledge financial support from the National Institute of Health under grant no. 5R01 EB002016-19, and the Department of Energy under grant no. DE-FG-02-06ER15803. The authors thank Richard Caprioli for suggesting the use of image fusion in SIMS, as well as Jordan Lerach for preparing and Hua Tian for obtaining SEM and SIMS images of gold-coated grid samples.
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Tarolli, J.G., Jackson, L.M. & Winograd, N. Improving Secondary Ion Mass Spectrometry Image Quality with Image Fusion. J. Am. Soc. Mass Spectrom. 25, 2154–2162 (2014). https://doi.org/10.1007/s13361-014-0927-7
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DOI: https://doi.org/10.1007/s13361-014-0927-7