DocumentCode :
706040
Title :
Automatic method for caveolar structure detection and intensity distribution analysis from microscopy images
Author :
Polonen, Harri ; Jansen, Maurice ; Tohka, Jussi ; Ikonen, Elina ; Ruotsalainen, Ulla
Author_Institution :
Inst. Signal Process., Tampere Univ. of Technol., Tampere, Finland
fYear :
2007
fDate :
3-7 Sept. 2007
Firstpage :
1107
Lastpage :
1111
Abstract :
Fluorescent fusion proteins of caveolin oligomerize to form plasma membrane pits, called caveolae. Amount of caveolin protein in a pit can be estimated by fluorescence intensity of the pit in microscopy image. In this study an automatic method is introduced for pit recognition, intensity measurement and intensity distribution parameter estimation. Dots are recognised and separated from non-caveolar structures. Intensities are measured with a new automatic method, which is capable of estimating intensities from all the recognised pits. Intensity distribution is cleaned up from outliers and modelled with a mixture model of normal distributions. Optimal parameter set of mixture model is searched automatically with a genetic algorithm.
Keywords :
biological techniques; biology computing; biomembranes; cellular biophysics; fluorescence spectroscopy; genetic algorithms; image recognition; optical microscopy; automatic method; caveolar structure detection; caveolin; fluorescence intensity; fluorescent fusion proteins; genetic algorithm; intensity distribution analysis; intensity distribution parameter estimation; intensity measurement; microscopy images; noncaveolar structures; oligomerisation; pit recognition; plasma membrane pits; Data models; Europe; Genetic algorithms; Microscopy; Proteins; Signal processing; Signal processing algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Conference, 2007 15th European
Conference_Location :
Poznan
Print_ISBN :
978-839-2134-04-6
Type :
conf
Filename :
7098976
Link To Document :
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