An automatic cell segmentation method for differential interference contrast microscopy

Proceedings - International Conference on Pattern Recognition

Volumn , Issue , 2008, Pages

  Kuijper, Arjan ^a   Heise, Bettina ^b  

^a JOHANN RADON INSTITUTE FOR COMPUTATIONAL AND APPLIED MATHEMATICS   (Austria)

^b JOHANNES KEPLER UNIVERSITY LINZ   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

CELLS; CYTOLOGY; NUMERICAL METHODS; PATTERN RECOGNITION;

AUTOMATIC METHOD; AUTOMATIC SEGMENTATIONS; BIO-IMAGING; CELL SEGMENTATION; DIFFERENTIAL INTERFERENCE CONTRAST MICROSCOPY; INDIVIDUAL CELLS; PHASE GRADIENT; SUB-STRUCTURES;

IMAGE SEGMENTATION;

EID: 77957949598     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/icpr.2008.4761747     Document Type: Conference Paper

References (13)

1. H. Chang, Q. Yang, and B. Parvin. Segmentation of heterogeneous blob objects through voting and level set formulation. Pattern Recognition Letters, 28(13):1781- 1787, 2007.
2. B. Heise and B. Arminger. Some aspects about quantitative reconstruction for differential interference contrast (dic) microscopy. In Proceedings of ICIAM07, 2007.
3. A. Kuijper, B. Heise, Y. Zhou, L. He, H. Wolinski, and S. Kohlwein. Segmentation of clustered cells in microscopy images by geometric pdes and level sets. In N. Paragios, J. Duncan, and N. Ayache, editors, Handbook of Biomedical Imaging. Springer, 2008.
4. R. Malladi. Geometric Methods in Bio-Medical Image Processing. Springer, 2002.
5. S. Osher and N. Paragios. Geometric Level Set Methods in Imaging, Vision, and Graphics. Springer, 2003.
6. S. Osher and J. Sethian. Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations. J. of Comp. Physics, 79:12-49, 1988.
7. B. Parvin, Q. Yang, J. Han, H. Chang, B. Rydberg, and M. Barcellos-Hoff. Iterative voting for inference of structural saliency and characterization of subcellular events. IEEE Trans Image Process., 16(3):615-623, 2007.
8. C. Preza. Rotational-diversity phase estimation from differential- interference-contrast microscopy images. J. of the Opt. Soc. of America A, 17(3):415-424, 2000.
9. O. Scherzer. Convergence criteria of iterative methods based on landweber iteration for solving nonlinear problems. J. Math. Anal. Appl., pages 911-933, 1995.
10. J. Sethian. Level set methods and fast marching methods. Cambridge University Press, Cambridge, UK, 1999.
11. C. Solorzano, R. Malladi, S. Lelievre, and S. Lockett. Segmentation of nuclei and cells using membrane related protein markers. Journal of Microscopy, 201:404- 415, 2001.
12. Q. Yang, B. Parvin, and M. Barcellos-Hoff. Localization of saliency through iterative voting. In ICPR (1), pages 63-66, 2004.
13. Y. Zhou, A. Kuijper, B. Heise, and L. He. Cell segmentation using the level set method. Technical Report 2007-17, RICAM, 2007. http://www.ricam.oeaw. ac.at/publications/reports/.