A Quantification Tool to Analyse Stained Cell Cultures

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3212, Issue , 2004, Pages 84-91

  Glory, E ^a   Faure, A ^b   Meas Yedid, V ^c   Cloppet, F ^a,b   Pinset, Ch ^a,c   Stamon, G ^b,c   Olivo Marin, J Ch ^a  

^a UNIVERSITÉ PARIS DESCARTES   (France)

^b INSTITUT PASTEUR   (France)

^c Biotop Pasteur   (France)

Author keywords

[No Author keywords available]

Indexed keywords

CELL CULTURE; CYTOLOGY; DECISION TREES; IMAGE PROCESSING;

BINARY OBJECTS; CELL FUNCTIONS; CLASSIFICATION METHODS; COLOR COMPONENT; CULTURE MEDIA; DIFFERENT SHAPES; METHOD OF CELLS; THRESHOLDING;

CELLS;

EID: 35048836665     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-30126-4_11     Document Type: Article

References (15)

1. Bamford, P.: Segmentation of cell images with an application to cervical cancer screening. PhD thesis - University of Queenland (1999)
2. Bitter, E., Benassarou, A., Lucas, L., Elias, L., Tchelidze, P., Ploton, D., O'Donohue, M.-F.: Analyse et Modélisation à l'Intérieur de Cellules Vivantes dans des Images 4D. R.P.I.A. 14ème Congrès Francophone AFRIF-AFIA, Toulouse, France (2004) 845-854
3. Brenner, J.J., Necheles, T.F., Bonacossa, I.A., Necheles, T.F., Fristensky, R., Weintraub, B.A., Neurath, P.W.: Scene segmentation techniques for the analysis of routine bone marrow smears from acute lymphoblastic leukaemia patients. Journal of Histochemistry and Cytochemistry 25-7 (1977) 601-613
4. Cloppet, F., Oliva, J.M., Stamon, G.: Angular Bisector Network, a Simplified Generalized Voronoï Diagram: Application to Processing Complex Intersections in Biomedical Images. IEEE Trans, on Pattern Analysis and Machine Intelligence 22-1 (2000) 120-128
5. Fernandez, G., Kunt, M., Zryd, J.-P.: Multi-spectral based cell segmentation and analysis. Proc. of the Workshop on Physics-based Modeling in Computer Vision, Cambridge, USA (1995) 166-172
6. Gonzalez, R.C., Wintz, P.: Digital Image Processing. Addison Wesley (1987) 122-125, 392-394
7. Rasband, W.: ImageJ, Version 1.31s. National Institues of Health, USA (2004) http://rsb.info.nih.gov/ij/
8. Lezoray, O., Elmoataz, A., Cardot, H., Revenu, M. : A.R.T.I.C : Un système automatique de tri cellulaire par Analyse d'images. Vision Interface (1999) 312-319
9. Meas-Yedid, V., Glory, E., Pinset, Ch., Stamon, G., Olivo-Marin, J-Ch.: Automatic color space selection for biological image segmentation. International Conference of Pattern Recognition (2004) to appear
10. Pal, N. R., Pal, S. K.: A review on image segmentation techniques. Pattern Recognition 26-9 (1993) 1277-1294
11. Ridler, T.W., CalvardClarke, S. : Picture thresholding using an iterative selection method. IEEE Trans. System, Man and Cybernetics 8 (1978) 630-632
12. Theodoridis, S., Koutroumbas, K.: Pattern Recognition. Accademic Press (1999) 13-20
13. Vincent, L., Soille, P.: Watersheds in digital spaces: an efficient algorithm based on immersion simulations. IEEE Trans, on Pattern Analysis and Machine Intelligence 13-6 (1991) 583-598
14. Xie, X., Mirmehdi, M.: Level-set based geometric color snakes with region support. Proc. of International Conference on Image Processing 2 (2003) 153-156
15. Zimmer, C., Labruyère, E., Meas-Yedid, V., Guillèn, N., Olivo-Marin, J.-Ch.: Improving active contours for segmentation and tracking of motile cells in videomicroscopy. 16th International Conference on Pattern Recognition, 2 (2002) 286-289