Title :
Localization of Drosophila embryos using connected components in scale space
Author :
Bessinger, Z. ; Guangming Xing ; Qi Li
Author_Institution :
Dept. of Math. & Comput. Sci., Western Kentucky Univ., Bowling Green, KY, USA
fDate :
Sept. 30 2012-Oct. 3 2012
Abstract :
Localization of Drosophila embryos in images is a fundamental step in an automatic computational system for the exploration of gene-gene interaction on Drosophila. In this paper, we introduce a localization framework based on the analysis of connected components in the Gaussian scale space of an embryonic image. We propose three criteria for the selection of the optimal scale. The experiment results show the promise of the proposed methods.
Keywords :
Gaussian processes; biology computing; genetics; image processing; Drosophila embryo localization; Gaussian scale space; automatic computational system; connected components analysis; embryonic image; gene-gene interaction; localization framework; optimal scale selection; Bioinformatics; Embryo; Feature extraction; Gene expression; Mathematical model; Minimization; Shape; Localization; connected component; scale selection;
Conference_Titel :
Image Processing (ICIP), 2012 19th IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4673-2534-9
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2012.6466905
