Overlapping nuclei segmentation based on Bayesian networks and stepwise merging strategy

Journal of Microscopy

Volumn 235, Issue 2, 2009, Pages 188-198

  Jeong, M R ^a   Ko, B C ^a   Nam, J Y ^a  

^a Keimyung University   (South Korea)

Author keywords

Bayesian networks; FISH; Nuclei classification; Stepwise merging; Watershed

Indexed keywords

DISTRIBUTION FUNCTIONS; FLUORESCENCE; FLUORESCENCE MICROSCOPY; GAUSSIAN DISTRIBUTION; IMAGE SEGMENTATION; MERGING; WATERSHEDS;

BAYESIA N NETWORKS; CELL NUCLEUS; FLUORESCENCE IN-SITU HYBRIDIZATION IMAGES; GAUSSIAN MIXTURE MODEL; LIKELIHOOD FUNCTIONS; MERGING STRATEGY; NEW APPROACHES; NUCLEUS CLASSIFICATION; OVERLAPPING NUCLEI SEGMENTATIONS; STEPWISE MERGING;

BAYESIAN NETWORKS;

ALGORITHM; ANALYTIC METHOD; ARTICLE; BAYES THEOREM; CELL NUCLEUS; CELL STRUCTURE; CELL ULTRASTRUCTURE; CELLULAR DISTRIBUTION; FLUORESCENCE IN SITU HYBRIDIZATION; IMAGE ANALYSIS; MOLECULAR IMAGING; NORMAL DISTRIBUTION; PRIORITY JOURNAL; PROBABILITY;

EID: 68349160341     PISSN: 00222720     EISSN: 13652818     Source Type: Journal    
DOI: 10.1111/j.1365-2818.2009.03199.x     Document Type: Article

References (15)

1. Adiga, P.S. & Chaudihuri, B.B. (2001) An efficient method based on watershed and rule-based merging for segmentation of 3-D histo-pathological images. Pattern Recognit. 34, 1449 1458.
2. Awate, S.P. (2006) Adaptive nonparametric Markov models and information-theoretic methods for image restoration and segmentation. PhD Thesis, University of Utah, Utah.
3. Charniak, E. (1991) Bayesian networks without tears. AI Mag. 12, 50 63.
4. Chen, X., Zhou, X. & Wongm, S. (2006) Automated segmentation, classification and tracking of cancer cell nuclei in time-lapse microscopy. IEEE Trans. Biomed. Eng. 53, 762 766.
5. Clocksin, W.F. (2003) Automatic segmentation of overlapping nuclei with high background variation using robust estimation and flexible contour models. Proceedings of the 12th International Conference on Image Analysis and Processing, vol. 1, pp. 682 687. Mantova, Italy.
6. Duchene, P. & Lewis, D. (1996) Marker finding algorithm. Visilog 5 Documentation, 1 st edn. Noesis Vision, Quebec, Canada.
7. Fernandez, G., Kunt, M. & Zryd, J-P. (1995) A new plant cell image segmentation algorithm. Proceeding of the 8th International Conference on Image Analysis and Processing, LNCS 974, pp. 229 234. San Remo, Italy.
8. Gonzalez, R.C. & Woods, R.E. (2007) Moment invariants. Digital Image Processing, 3rd edn, pp. 839 842. Prentice Hall: Upper Saddle River.
9. Lerner, B., Clocksin, W.F., Dhanjal, S., Hultén, M.A. & Bishop, C.M. (2001) Automatic signal classification in fluorescence in situ hybridization images. Cytometry 43A, 87 93.
10. Lin, G., Adiga, U., Olson, Guzowski, J., Barnes, C. & Roysam, B. (2003) A hybrid 3D watershed algorithm incorporating gradient cues and object models for automatic segmentation of nuclei in confocal image stacks. Cytometry 56A, 23 36.
11. Malpica, N., Solorzano, C., Vaquero, J.J., Santos, A., Vallcorba, I., Sagredo, J.G. & Pozol, F. (1997) Applying watershed algorithms to the segmentation of clustered nuclei. Cytometry 28, 289 297.
12. Otsu, N. (1979) A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. SMC-9, 62 66.
13. Raman, S., Maxwell, C.A. & Barcellos-Hoff, M.H. (2007) Geometric approach to segmentation and protein localization in cell culture assays. J. Microsc. 225, 22 30.
14. Restif, C. (2006) Towards safer, faster prenatal genetic tests: novel unsupervised, automatic and robust methods of segmentation of nuclei and probes. Proceedings of the European Conference on Computer Vision, vol. 3951, pp. 437 450. Graz, Austria.
15. Restif, C. & Clocksin, W.F. (2004) Comparison of segmentation methods for cytometric assay. Proceeding of the International Conference on Medical Image Understanding and Analysis, pp. 153 156. London, UK.