Variational attenuation correction in two-view confocal microscopy

BMC Bioinformatics

Olaf Ronneberger⁴  Klaus Palme¹  Thomas Blein²  Margret Keuper⁵  Jasmin Dürr³  Thorsten Schmidt⁵ 

[1]FRISYS, Faculty for Biology, Albert-Ludwigs-Universität Freiburg, Albertstr. 19, 79104 Freiburg, Germany

[2]Current address: Institut Jean-Pierre Bourgin, Unité Mixte de Recherche 1318, Institut National de la Recherche Agronomique-AgroParisTech, Bâtiment 2, INRA Centre de Versailles-Grignon, 78026 Versailles Cedex, France

[3]Institute of Biology II, Albert-Ludwigs-Universität, Schänzlestr. 1, 79104 Freiburg, Germany

[4]BIOSS, Centre for Biological Signalling Studies, Albert-Ludwigs-Universität, Albertstr. 19, 79104 Freiburg, Germany

[5]Department of Computer Science, Albert-Ludwigs-Universität, Georges-Köhler-Allee Geb. 52, 79110 Freiburg, Germany

关键词: Calculus of variations;    Image restoration;    Confocal microscopy;    Absorption;    Attenuation correction;   

Others  :  1087672
DOI  :  10.1186/1471-2105-14-366

 received in 2013-03-22, accepted in 2013-11-29,  发布年份 2013

【 摘 要 】

Background

Absorption and refraction induced signal attenuation can seriously hinder the extraction of quantitative information from confocal microscopic data. This signal attenuation can be estimated and corrected by algorithms that use physical image formation models. Especially in thick heterogeneous samples, current single view based models are unable to solve the underdetermined problem of estimating the attenuation-free intensities.

Results

We present a variational approach to estimate both, the real intensities and the spatially variant attenuation from two views of the same sample from opposite sides. Assuming noise-free measurements throughout the whole volume and pure absorption, this would in theory allow a perfect reconstruction without further assumptions. To cope with real world data, our approach respects photon noise, estimates apparent bleaching between the two recordings, and constrains the attenuation field to be smooth and sparse to avoid spurious attenuation estimates in regions lacking valid measurements.

Conclusions

We quantify the reconstruction quality on simulated data and compare it to the state-of-the art two-view approach and commonly used one-factor-per-slice approaches like the exponential decay model. Additionally we show its real-world applicability on model organisms from zoology (zebrafish) and botany (Arabidopsis). The results from these experiments show that the proposed approach improves the quantification of confocal microscopic data of thick specimen.

【 授权许可】

   
2013 Schmidt et al.; licensee BioMed Central Ltd.

【 图 表 】

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【 参考文献 】

• [1]Egner A, Hell SW: Aberrations in confocal and multi-photon fluorescence microscopy induced by refractive index mismatch. In Handbook of Biological Confocal Microscopy. Edited by Pawley JB. New York: Springer; 2006:404-413.
• [2]Booth M, Neil M, Wilson T: Aberration correction for confocal imaging in refractive-index-mismatched media. J Microsc 1998, 192(2):99-98.
• [3]Guan YQ, Cai YY, Zhang X, Lee YT, Opas M: Adaptive correction technique for 3D reconstruction of fluorescence microscopy images. Microsc Res Techn 2008, 71(2):146-157.
• [4]Čapek M, Janáček J, Kubínová L: Methods for compensation of the light attenuation with depth of images captured by a confocal microscope. Microsc Res Tech 2006, 69(8):624-635.
• [5]Stanciu SG, Stanciu GA, Coltuc D: Automated compensation of light attenuation in confocal microscopy by exact histogram specification. Microc Res Tech 2010, 73:165-175.
• [6]Can A, Al-kofahi O, Lasek S, Szarowski DH, Turner JN, Roysam B: Attenuation correction in confocal laser microscopes: a novel two-view approach. J Microsc 2003, 211:67-79.
• [7]Ronneberger O, Liu K, Rath M, Rueß D, Mueller T, Skibbe H, Drayer B, Schmidt T, Filippi A, Nitschke R, Brox T, Burkhardt H, Driever W: ViBE-Z: a framework for 3D virtual colocalization analysis in Zebrafish Larval Brains. Nature Methods 2012, 9(7):735-742.
• [8]Visser T, Groen F, Brakenhoff G: Absorption and scattering correction in fluorescence confocal microscopy. J Microsc 1991, 163(2):189-200.
• [9]Schmidt T, Dürr J, Keuper M, Blein T, Palme K, Ronneberger O: Variational attenuation correction of two-view confocal microscopic recordings. In IEEE International Symposium on Biomedical Imaging (ISBI). San Francisco, CA, USA. Piscataway: IEEE; 2013:169-172.
• [10]Foi A, Trimeche M, Katkovnik V, Egiazarian K: Practical poissonian-gaussian noise modeling and fitting for single-image raw-data. Trans Image Process 2008, 17(10):1737-1754. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4623175&tag=1 webcite
• [11]Zhu C, Byrd RH, Lu P, Nocedal J: Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization. ACM Trans Math Softw 1997, 23(4):550-560.
• [12]Brox T: Von Pixeln zu Regionen: Partielle Differenzialgleichungen in der Bildanalyse. PhD thesis,Universität des Saarlandes, Mathematische Bildverarbeitungsgruppe, Fakultät für Mathematik und Informatik Universität des Saarlandes, 66041 Saarbrücken. 2005. http://lmb.informatik.uni-freiburg.de/people/brox/pub/brox_PhDThesis.pdf webcite
• [13]Shepp LA, Logan BF: The fourier reconstruction of a head section. IEEE Trans Nuclear Science 1974, 21(3):21-43. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6499235&tag=1 webcite