Issue No. 06 - November/December (2011 vol. 8)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TCBB.2011.37
Qi Li , Western Kentucky University, Bowling Green
Chandra Kambhamettu , University of Delaware, Newark
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.
Contour extraction, embryonic images, statistics learning, image points.
Q. Li and C. Kambhamettu, "Contour Extraction of Drosophila Embryos," in IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 8, no. , pp. 1509-1521, 2011.