



@conference {2219,
	title = {Low frame rate cell tracking: A Delaunay graph matching approach},
	booktitle = {Proceedings - International Symposium on Biomedical ImagingIEEE Comput. Soc. Conf. Comput. Vis. Pattern Recogn.},
	series = {2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI{\textquoteright}11},
	year = {2011},
	note = {Conference code: 87101Export Date: 21 November 2012Source: ScopusArt. No.: 5872573doi: 10.1109/ISBI.2011.5872573Language of Original Document: EnglishCorrespondence Address: Chen, Y.; INEB - Instituto de Engenharia Biom{\'e}dica, Rua do Campo Alegre, 823, 4150-180 Porto, PortugalReferences: Godinez, W.J., Lampe, M., Worz, S., Muller, B., Eils, R., Rohr, K., Tracking of virus particles in time-lapse fluorescence microscopy image sequences (2007) Proceedings of the IEEE International Symposium on Biomedical Imaging, pp. 256-259;Finch, A.W., Wilson, R.C., Hancock, E.R., Symbolic graph matching with the em algorithm (1998) Pattern Recognit, 31 (11), pp. 1777-1790. , Nov; 
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Quelhas, P., Marcuzzo, M., Mendon{\c c}a, A.M., Campilho, A., Cell nuclei and cytoplasm joint segmentation using the sliding band filter (2010) IEEE Transactions on Medical Imaging, 29, pp. 1463-1473; 
Fortune, S., A sweepline algorithm for voronoi diagram (1987) Algorithmica, 2, pp. 153-174; 
Khoo, K., Suganthan, P., Evaluation of genetic operators and solution representations for shape recognition by genetic algorithms (2002) Patt. Recognit. Lett., 23 (13), pp. 1589-1597; 
Caetano, T.S., Caelli, T., Schuurmans, D., Barone, D., Graphical models and point pattern matching (2006) IEEE Trans. on Pattern Analysis and Machine Intelligence, 28 (10), pp. 1646-1662. , Oct; 
Raveaux, R., Burie, J.-C., Ogier, J.-M., A graph matching method and a graph matching distance based on subgraph assignments (2010) Pattern Recognition Letters, 31, pp. 394-406; 
Marcuzzo, M., Quelhas, P., Campilho, A., Cell division detection on the arabidopsis thaliana root (2009) IbPRIA 2009, 5524, pp. 168-175. , LNCS
Sponsors: Inst. Electr. Electron. Eng., Eng. Med. Biol. Soc. (IEEE EMBS); Inst. Electr. Electron. Eng., Signal Process. Soc. (IEEE SPS)},
	month = {2011///},
	pages = {1015 - 1018},
	address = {Chicago, IL},
	abstract = {Cell tracking is a fundamental problem for studying live cell dynamics. A novel approach for low frame rate cell tracking in fluorescent microscopy image is herein proposed. The method is based on sliding band filter detection and Delaunay triangulation sub-graph matching. With this approach we can track a large amount of small cells without their motion model and not relying on cell motion continuity between consecutive images. The effectiveness and robustness of the method were validated by visual inspection and on a ground truth dataset. {\textcopyright} 2011 IEEE.},
	keywords = {Band filters, cell motion, Cell tracking, Cells, Consecutive images, Data sets, Delaunay graph, Delaunay graph matching, Delaunay triangulation, Fluorescent microscopy, Frame rate, Fundamental problem, Ground truth, Live cell, low frame rate tracking, Medical imaging, Motion models, small target tracking, Small targets, Target tracking, Visual inspection},
	isbn = {19457928 (ISSN); 9781424441280 (ISBN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-80055027991\&partnerID=40\&md5=f347799ea22097a5550939fa287cd4ab},
	author = {Chen, Y. and Quelhas, P. and Campilho, A.}
}
