DocumentCode :
1458480
Title :
Contour Extraction of Drosophila Embryos
Author :
Li, Qi ; Kambhamettu, Chandra
Author_Institution :
Dept. of Math. & Comput. Sci., Western Kentucky Univ., Bowling Green, KY, USA
Volume :
8
Issue :
6
fYear :
2011
Firstpage :
1509
Lastpage :
1521
Abstract :
Contour extraction of Drosophila (fruit fly) embryos is an important step to build a computational system for matching expression pattern of embryonic images to assist the discovery of the nature of genes. Automatic contour extraction of embryos is challenging due to severe image variations, including 1) the size, orientation, shape, and appearance of an embryo of interest; 2) the neighboring context of an embryo of interest (such as nontouching and touching neighboring embryos); and 3) illumination circumstance. In this paper, we propose an automatic framework for contour extraction of the embryo of interest in an embryonic image. The proposed framework contains three components. Its first component applies a mixture model of quadratic curves, with statistical features, to initialize the contour of the embryo of interest. An efficient method based on imbalanced image points is proposed to compute model parameters. The second component applies active contour model to refine embryo contours. The third component applies eigen-shape modeling to smooth jaggy contours caused by blurred embryo boundaries. We test the proposed framework on a data set of 8,000 embryonic images, and achieve promising accuracy (88 percent), that is, substantially higher than the-state-of-the-art results.
Keywords :
bioinformatics; biological techniques; cellular biophysics; genetics; image processing; microorganisms; physiological models; Drosophila embryos; active contour model; automatic contour extraction; blurred embryo boundaries; computational system; eigen-shape modeling; embryo contours; embryonic imaging; genes; image variations; imbalanced image points; mixture model; model parameters; quadratic curves; smooth jaggy contours; statistical features; Active contours; Context awareness; Embryo; Feature extraction; Image edge detection; Image segmentation; Learning systems; Contour extraction; embryonic images; image points.; statistics learning; Algorithms; Animals; Computational Biology; Drosophila; Embryo, Nonmammalian; Image Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Computational Biology and Bioinformatics, IEEE/ACM Transactions on
Publisher :
ieee
ISSN :
1545-5963
Type :
jour
DOI :
10.1109/TCBB.2011.37
Filename :
5719605
Link To Document :
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