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Identification of Cell-Cycle Phases Using Neural Network and Steerable Filter Features

  • Xiaodong Yang
  • Houqiang Li
  • Xiaobo Zhou
  • Stephen T. C. Wong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3973)

Abstract

In this paper, we aim to address the cell phase identification problem, and two important aspects, the feature extraction methods and the classifier design, are discussed. In our study, we first propose extracting high frequency information of different orientations using Steerable filters. Next, we employ a multi-layer neural network using the back-propagation algorithm to replace K-Nearest Neighbor (KNN) classifier which has been implemented in the Cellular Image Quantitator (CELLIQ) system [3]. Experimental results provide a comparison between the proposed steerable filter features and existing regular features which have been used in published papers [3, 5]. From the comparison, it can be concluded that Steerable filter features can effectively represent the cells in different phases and improve the classification accuracy. Neural network also has a better performance than KNN currently deployed in CELLIQ system [3].

Keywords

Classification Accuracy Hide Unit Zernike Moment Gabor Wavelet Regular Feature 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Yang, X., Li, H., Zhou, X., Wong, S.T.C.: Automated Segmentation and Tracking of Cells in Time-Lapse Microscopy Using Watershed and Mean Shift. In: International Symposium on Intelligent Signal Processing and Communication Systems, Hong Kong (In Press)Google Scholar
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    Chen, X., Zhou, X., Wong, S.T.C.: Automated Segmentation, Classification, and Tracking of Cancer Cell Nuclei in Time-Lapse Microscopy. IEEE Transactions on Biomedical Engineering (2006) (Accepted for Publication)Google Scholar
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Xiaodong Yang
    • 1
  • Houqiang Li
    • 1
  • Xiaobo Zhou
    • 2
  • Stephen T. C. Wong
    • 2
  1. 1.Department of Electronic Engineering and Information ScienceUniversity of Science and Technology of China 
  2. 2.Center for Bioinformatics, HCNRHarvard Medical SchoolBostonUSA

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