Skip to main content

Cell Division Detection on the Arabidopsis Thaliana Root

  • Conference paper
Pattern Recognition and Image Analysis (IbPRIA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5524))

Included in the following conference series:

  • 1855 Accesses

Abstract

The study of individual plant cells and their growth structure is an important focus of research in plant genetics. To obtain development information at cellular level, researchers need to perform in vivo imaging of the specimen under study, through time-lapse confocal microscopy. Within this research field it is important to understand mechanisms like cell division and elongation of developing cells. We describe a tool to automatically search for cell division in the Arabidopsis thaliana using information of nuclei shape. The nuclei detection is based on a convergence index filter. Cell division detection is performed by an automatic classifier, trained through cross-validation. The results are further improved by a stability criterion based on the Mahalanobis distance of the shape of the nuclei through time. With this approach, we can achieve a correct detection rate of 94.7%.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Campilho, A., Garcia, B., Toorn, H., Wijk, H., Campilho, A., Scheres, B.: Time-lapse analysis of stem-cell divisions in the arabidopsis thaliana root meristem. The Plant Journal 48, 619–627 (2006)

    Article  Google Scholar 

  2. Iwamoto, A., Satoh, D., Furutani, M., Maruyama, S., Ohba, H., Sugiyama, M.: Insight into the basis of root growth in arabidopsis thaliana provided by a simple mathematical model. J. Plant Res. 119, 85–93 (2006)

    Article  Google Scholar 

  3. Roberts, T., Mckenna, S., Wuyts, N., Valentine, T., Bengough, A.: Performance of low-level motion estimation methods for confocal microscopy of plant cells in vivo. In: Motion 2007, p. 13 (2007)

    Google Scholar 

  4. Beemster, G., Baskin, T.: Analysis of cell division and elongation underlying the developmental acceleration of root growth in arabidopsis thaliana. Plant Physiology 116, 1515–1526 (1998)

    Article  Google Scholar 

  5. Chen, X., Zhou, X., Wong, S.T.C.: Automated segmentation, classification, and tracking of cancer cell nuclei in time-lapse microscopy. IEEE Trans. on Biomedical Engineering 53(4), 762–766 (2006)

    Article  Google Scholar 

  6. Mao, K.Z., Zhao, P., Tan, P.: Supervised learning-based cell image segmentation for p53 immunohistochemistry. IEEE Trans. on Biomedical Engineering 53(6), 1153–1163 (2006)

    Article  Google Scholar 

  7. Yang, X., Li, H., Zhou, X.: Nuclei segmentation using marker-controlled watershed, tracking using mean-shift, and kalman filter in time-lapse microscopy. IEEE Trans. on Circuits and Systems I-Regul. Papers 53(11), 2405–2414 (2006)

    Article  Google Scholar 

  8. Harder, N., M-Bermudez, F., Godinez, W., Ellenberg, J., Eils, R., Rohr, K.: Automated analysis of mitotic cell nuclei in 3d fluorescence microscopy image sequences. In: Workshop on Bio-Image Informatics: Biological Imaging, Computer Vision and Data Mining (2008)

    Google Scholar 

  9. Kobatake, H., Hashimoto, S.: Convergence index filter for vector fields. IEEE Trans. on Image Processing 8(8) (1999)

    Google Scholar 

  10. Wei, J., Hagihara, Y., Kobatake, H.: Detection of rounded opacities on chest radiographs using convergence index filter. In: Proceedings of the Int. Conference on Image Analysis and Processing, pp. 757–761 (1999)

    Google Scholar 

  11. Pereira, C.S., Fernandes, H., Mendonça, A.M., Campilho, A.C.: Detection of lung nodule candidates in chest radiographs. In: Martí, J., Benedí, J.M., Mendonça, A.M., Serrat, J. (eds.) IbPRIA 2007. LNCS, vol. 4478, pp. 170–177. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  12. Marcuzzo, M., Quelhas, P., Campilho, A., Mendonça, A.M., Campilho, A.: A hybrid approach for cell image segmentation. In: Campilho, A., Kamel, M.S. (eds.) ICIAR 2008. LNCS, vol. 5112, pp. 739–749. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Marcuzzo, M., Guichard, T., Quelhas, P., Mendonça, A.M., Campilho, A. (2009). Cell Division Detection on the Arabidopsis Thaliana Root. In: Araujo, H., Mendonça, A.M., Pinho, A.J., Torres, M.I. (eds) Pattern Recognition and Image Analysis. IbPRIA 2009. Lecture Notes in Computer Science, vol 5524. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02172-5_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-02172-5_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02171-8

  • Online ISBN: 978-3-642-02172-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics