Three-dimensional reconstruction methods for micro-rotation fluorescence microscopy

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Laksameethanasan, Danai
dc.date.accessioned 2012-08-21T12:31:36Z
dc.date.available 2012-08-21T12:31:36Z
dc.date.issued 2009
dc.identifier.isbn 978-951-22-9755-9
dc.identifier.isbn 978-951-22-9754-2 (printed) #8195;
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/4591
dc.description.abstract Micro-rotation fluorescence microscopy is a novel, optical imaging technique developed with a cell rotation system. The imaging system enables individual living cells to be rotated in suspension under microscopic dimensions, and allows us to acquire a series of images of the cells, simultaneously during the rotation. A challenging task in micro-rotation imaging is how to determine three-dimensional (3D) cell structure from the image series. This thesis thus presents four alternative methods for reconstructing 3D objects from a series of micro-rotation images. The three former methods, the expectation maximisation (EM), the generalised Skilling-Bryan and the marginalisation methods, are iterative algorithms built on the Bayesian inversion theory, which is used to quantify uncertainties in data and model parameters, and also to utilise prior information about the unknown structure. The fourth method, dual filtered backprojection (DFBP), is a fast, non-iterative algorithm derived from the Fourier slice theorem in the classical computed tomography. Each method has its own features: the EM method serves as a basic tool for general usability; the Skilling-Bryan method is more flexible for modelling of noise and prior; the marginalisation method serves as a statistical treatment of the reconstruction that suffers from inaccurate image alignment; and the DFBP method beats the other methods by computational speed but restricts itself with a certain imaging condition. In general, selection of the reconstruction methods depends on imaging and data conditions, such as conventional widefield or confocal microscopy, the stability of cell rotation, and the quality of image alignment. In conclusion, all the proposed reconstruction methods clearly increase capability to visualise 3D object structures, as shown by both simulations and experiments with real micro-rotation data. Two obvious messages from the results are that first, the quality of the reconstructed object highly depends on the accuracy of image alignment, and second, micro-rotation reconstructions with the current imaging system always contain poor resolution in the tangential direction of the rotation. Future interesting research is thus to combine the micro-rotation protocol with extended depth-of-focus microscopy that could strengthen the tangential resolution. en
dc.format.extent Verkkokirja (2602 KB, 59 s.)
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Teknillinen korkeakoulu en
dc.relation.haspart [Publication 1]: D. Laksameethanasan, S. S. Brandt, and P. Engelhardt. 2006. A three-dimensional Bayesian reconstruction method with the point spread function for micro-rotation sequences in wide-field microscopy. In: Proceedings of the 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2006). Arlington, VA, USA. 6-9 April 2006, pages 1276-1279. © 2006 IEEE. By permission. en
dc.relation.haspart [Publication 2]: Danai Laksameethanasan and Sami S. Brandt. 2007. Generalised Skilling–Bryan minimisation for micro-rotation imaging in light microscopy. In: Kevin H. Knuth, Ariel Caticha, Julian L. Center Jr., Adom Giffin, and Carlos C. Rodríguez (editors). Proceedings of the 27th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2007). Saratoga Springs, New York, USA. 8-13 July 2007. AIP Conference Proceedings, volume 954, pages 354-361. © 2007 American Institute of Physics. By permission. en
dc.relation.haspart [Publication 3]: Danai Laksameethanasan, Sami S. Brandt, Peter Engelhardt, Olivier Renaud, and Spencer L. Shorte. 2008. A Bayesian reconstruction method for micro-rotation imaging in light microscopy. Microscopy Research and Technique, volume 71, number 2, pages 158-167. en
dc.relation.haspart [Publication 4]: Danai Laksameethanasan and Sami S. Brandt. 2009. A Bayesian reconstruction method with marginalised uncertainty model for camera motion in micro-rotation fluorescence microscopy. Helsinki University of Technology, Department of Biomedical Engineering and Computational Science Publications, Report A08. ISBN 978-951-22-9756-6. IEEE Transactions on Biomedical Engineering, submitted for publication. en
dc.relation.haspart [Publication 5]: Danai Laksameethanasan, Sami S. Brandt, Olivier Renaud, and Spencer L. Shorte. 2009. Dual filtered backprojection for micro-rotation confocal microscopy. Inverse Problems, volume 25, number 1, 015006. © 2009 Institute of Physics Publishing. By permission. en
dc.subject.other Physics en
dc.title Three-dimensional reconstruction methods for micro-rotation fluorescence microscopy en
dc.type G5 Artikkeliväitöskirja fi
dc.contributor.department Lääketieteellisen tekniikan ja laskennallisen tieteen laitos fi
dc.subject.keyword optical microscopy en
dc.subject.keyword micro-rotation imaging en
dc.subject.keyword deconvolution en
dc.subject.keyword tomography en
dc.subject.keyword image reconstruction en
dc.subject.keyword statistical inverse problems en
dc.subject.keyword cell biology en
dc.identifier.urn URN:ISBN:978-951-22-9755-9
dc.type.dcmitype text en
dc.type.ontasot Väitöskirja (artikkeli) fi
dc.type.ontasot Doctoral dissertation (article-based) en


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