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Data visualization, numerical & computational image analysis, software developmentThe facility provides state-of-the-art image processing and visualization
software packages such as for direct volume rendering, polygone-based 3D reconstruction, object modeling, image quantification and image deconvolution.
In collaboration with external institutions we evaluate images processing routines for yeast applications such as for automated registration of yeast cells in differential interference contrast (DIC) images as well as for cluster analysis of acquired yeast screening data (Bettina Heise, FLLL-Linz).
In addition, we use features of amira (http://www.amiravis.com), a highly modular commercially available software system for designing custom software extensions for visualization and quantification of multi-dimensional image data. amira provides sophisticated scripting features using Tool Command Language (Tcl) as well as provides features for implementation of C++ and Matlab routines. In this context, we have recently developed HCS Profiler a novel software for automated visualization and quantification of multi-channel 3D image data derived from screening approaches.
Scripting-customized software tools
Quadruple viewer system of "QuantIT", a scripting-customized software tool for quantification of three-dimensional yeast structures. Author: H. Wolinski. YGMBG-Graz.
Computational image analysis
Automated detection of cell areas in differential interference contrast (DIC) images.
Algorithm developed by Bettina Heise (1), FLLL-Linz.
Application of maximum likelihood estimation (MLE) image restoration method to improve image quality of confocal z-stacks. Image at left: "blurred" confocal raw data (SytoxGreen labeled mitochondrial DNA), image at right: processed data.
Polygon-based 3d reconstruction
Direct volume rendering
Mitochondrial structures (green) and lipid droplets (red)
Stereo images (click on images to enlarge; red/green glasses required)
Gravure of a metal pen imaged using reflection mode
References yeast cell registration:
#Heise B. et al. DIC-Image reconstruction with integrational methods and phase filtering for automated analysis of yeast cells ; in: Digital Imaging and Pattern Recognition, Band209, 30 th Workshop of OAGM /AAPR, 2006.
# Ohnuki S, Nogami S, Kanai H, Hirata D, Nakatani Y, Morishita S, Ohya Y. Diversity of Ca2+-induced morphology revealed by morphological phenotyping of Ca2+-sensitive mutants of Saccharomyces cerevisiae. Eukaryot Cell. 2007 Mar 9. (PubMed)
# Nogami S, Ohya Y, Yvert G. Genetic complexity and quantitative trait loci mapping of yeast morphological traits. PLoS Genet. 2007 Feb 23;3(2):e31. (PubMed)
# Kikuchi Y, Mizuuchi E, Nogami S, Morishita S, and Ohya, Y. Involvement of Rho-type GTPase in control of cell size in Saccharomyces cerevisiae. FEMS Yeast Research. 2007 Feb 16. (PubMed)
# Suzuki G, Sawai H, Ohtani M, Nogami S, Sano-Kumagai F, Saka A, Yukawa M, Saito T L, Sese J, Hirata D, Morishita S, and Ohya Y. Evaluation of image processing programs for accurate measurement of budding and fission yeast morphology. Curr Genet. 2006 Jan 6;:1-11
# Yoshikazu Ohya, Jun Sese(*), Masashi Yukawa(*), Fumi Sano, Yoichiro Nakatani, Taro L. Saito, Ayaka Saka, Tomoyuki Fukuda, Satoru Ishihara, Satomi Oka, Genjiro Suzuki, Machika Watanabe, Aiko Hirata, Miwaka Ohtani, Hiroshi Sawai, Nicolas Fraysse, Jean-Paul Latge, Jean M. Francois, Markus Aebi, Seiji Tanaka, Sachiko Muramatsu, Hiroyuki Araki, Kintake Sonoike, Satoru Nogami, and Shinichi Morishita. High-dimensional and large-scale phenotyping of yeast mutants. PNAS published December 19, 2005, 10.1073/pnas.0509436102 ( Genetics ) (* equally contributed authors) http://www.pnas.org/cgi/content/abstract/0509436102v1
# Data Mining Tools for The Saccharomyces Cerevisiae Morphological Database. Taro L. Saito(*), Jun Sese(*), Yoichiro Nakatani, Fumi Sano, Masashi Yukawa, Yoshikazu Ohya and Shinichi Morishita. Nucleic Acids Research 2005. Vol. 33 (Web Server Issue). (* equally contributed authors) http://nar.oxfordjournals.org/cgi/content/abstract/33/suppl_2/W753
# Masaya Suzuki, Ryoji Igarashi, Mizuho Sekiya, Takahiko Utsugi, Shinichi Morishita, Masashi Yukawa, Yoshikazu Ohya. Dynactin is involved in a checkpoint to monitor cell wall synthesis in Saccharomyces cerevisiae. Nature Cell Biology 6, 861 - 871, 2004.
# Miwaka Ohtani, Ayaka Saka, Fumi Sano, Yoshikazu Ohya, and Shinichi Morishita: Development of Image Processing Program for Yeast Cell Morphology. Journal of Bioinformatics and Computational Biology Vol. 1, No. 4 695-709, 2004.
#Taro L. Saito, Miwaka Ohtani, Hiroshi Sawai, Fumi Sano, Ayaka Saka, Daisuke Watanabe, Masashi Yukawa, Yoshikazu Ohya, and Shinichi Morishita. SCMD: Saccharomyces Cerevisiae Morphological Database. Nucl. Acids. Res. 32: D319-D322 (2004)
ntegrating high-throughput genetic interaction mapping and high-content screening to explore yeast spindle morphogenesis.
#Vizeacoumar FJ, van Dyk N, S Vizeacoumar F, Cheung V, Li J, Sydorskyy Y, Case N, Li Z, Datti A, Nislow C, Raught B, Zhang Z, Frey B, Bloom K, Boone C, Andrews BJ.
J Cell Biol. 2010 Jan 11;188(1):69-81.
#Carpenter, A. E., Jones, T. R., Lamprecht, M. R., Clarke, C., Kang, I. H., Friman, O., Guertin, D. A., Chang, J. H., Lindquist, R. A., Moffat, J., Golland, P., Sabatini, D. M., 2006. CellProfiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biol. 7, R100.
#Chen, S. C., Zhao, T., Gordon, G. J., Murphy, R. F., 2007. Automated image analysis of protein localization in budding yeast. Bioinformatics. 23, i66-71.
#Ohtani, M., Saka, A., Sano, F., Ohya, Y., Morishita, S., 2004. Development of image processing program for yeast cell morphology. J Bioinform Comput Biol. 1, 695-709.
#Gordon, A., Colman-Lerner, A., Chin, T. E., Benjamin, K. R., Yu, R. C., Brent, R., 2007. Single-cell quantification of molecules and rates using open-source microscope-based cytometry. Nat Methods. 4, 175-81.
#Kvarnstrom, M., Logg, K., Diez, A., Bodvard, K., Kall, M., 2008. Image analysis algorithms for cell contour recognition in budding yeast. Opt Express. 16, 12943-57.
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