Abstract
The work flow of cell biologists depends more and more on the analysis of a large number of images. The manual analysis is a tedious, time consuming and error-prone task. Therefore the aid of automatic image analysis would be beneficial. This however needs segmentation techniques which can handle low contrast noisy images with bleed-through from different fluorescent dyes. In this paper we propose a technique which can cope with these problems by using intensity statistics. The proposed techniques are validated conform the requirements for the ICIAR Arabidopsis Thaliana Root Cell Segmentation Challenge , which allows straight forward comparison of different techniques for segmentation of Arabidopsis nuclei.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Kuijper, A., Zhou, Y.Y., Heise, B.: Clustered cell segmentation - based on iterative voting and the level set method. In: Visapp 2008: Proceedings of the Third International Conference on Computer Vision Theory and Applications, vol. 1, pp. 307–314 (2008)
Ray, N., Acton, S.T.: Motion gradient vector flow: An external force for tracking rolling leukocytes with shape and size constrained active contours. IEEE Transactions on Medical Imaging 23(12), 1466–1478 (2004)
Ruberto, C., Dempster, A., Khan, S., Jarra, B.: Analysis of infected blood cell images using morphological operators. Image and Vision Computing 20, 133–146 (2002)
Vincent, L., Masters, B.: Morphological image-processing and network analysis of cornea endothelial-cell images. Image Algebra and Morphological Image Processing 1769, 212–226 (1992)
Carpenter, A., Jones, T., Lamprecht, M.R., Clarke, C., Kang, I., Friman, I., Guertin, D., Chang, J., Lindquist, R., Moffat, J., Colland, P., Sabatini, D.: Cellprofiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biology 7 (2006)
Megason, S.G., Fraser, S.E.: Digitizing life at the level of the cell: high-performance laserscanning microscopy and image analysis for in toto imaging of development. Mechanisms of Development 120(11), 1407–1420 (2003)
Unser, M.: The colored revolution of bio-imaging: New opportunities for signal processing. In: Fourteenth European Signal Processing Conference (EUSIPCO’06), Firenze, Italy. September 5-8 (2006); Tutorial
Chen, X.W., Zhou, X.B., Wong, S.T.C.: Automated segmentation, classification, and tracking of cancer cell nuclei in time-lapse microscopy. IEEE Transactions on Biomedical Engineering 53(4), 762–766 (2006)
Yu, D.G., Pham, T.D., Zhou, X.B., Wong, S.T.C.: Recognition and analysis of cell nuclear phases for high-content screening based on morphological features. Pattern Recognition 42(4), 498–508 (2009)
Li, G., Liu, T., Nie, J., Guo, L., Chen, J., Zhu, J., Xia, W., Mara, A., Holley, S., Wong, S.T.C.: Segmentation of touching cell nuclei using gradient flow tracking. Journal of Microscopy- Oxford 231(1), 47–58 (2008)
Cloppet, F., Boucher, A.: Segmentation of complex nucleus configurations in biological images. Pattern Recognition Letters (in press, 2010)
Marcuzzo, M., Quelhas, P., Mendonca, A.M., Campilho, A.: Evaluation of symmetry enhanced sliding band filter for plant cell nuclei detection in low contrast noisy fluorescent images. In: Kamel, M., Campilho, A. (eds.) ICIAR 2009. LNCS, vol. 5627, pp. 824–831. Springer, Heidelberg (2009)
Matlab: Correcting Nonuniform Illumination, http://www.mathworks.com/image-videoprocessing/demos.html?file=/products/demos/shipping/images/ipexrice.html
Xu, C., Prince, J.: Snakes, shapes and gradient vector flow. IEEE Transactions on Image Processing 7, 359–369 (1998)
De Bock, J., Philips, W.: Line segment based watershed segmentation. In: Gagalowicz, A., Philips, W. (eds.) MIRAGE 2007. LNCS, vol. 4418, pp. 579–586. Springer, Heidelberg (2007)
Wright Cell Imaging Facility: Particle Analysis, http://www.uhnresearch.ca/facilities/wcif/imagej/particle_analysis.htm
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
De Vylder, J., Rooms, F., Philips, W. (2010). Segmentation of Cell Nuclei in Arabidopsis Thaliana Roots. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2010. Lecture Notes in Computer Science, vol 6112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13775-4_21
Download citation
DOI: https://doi.org/10.1007/978-3-642-13775-4_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13774-7
Online ISBN: 978-3-642-13775-4
eBook Packages: Computer ScienceComputer Science (R0)