Iterative multilevel thresholding and splitting for three-dimensional segmentation of live cell nuclei using laser scanning confocal microscopy

Journal of Computer-Assisted Microscopy

Volumn 10, Issue 4, 1998, Pages 151-162

  Luo, D ^a   Barker, J ^a   McGrath, J C ^a   Daly, C J ^a  

^a UNIVERSITY OF GLASGOW   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BLOOD VESSELS; CELLS; COMPUTER APPLICATIONS; IMAGE SEGMENTATION; LASER APPLICATIONS; LASER TISSUE INTERACTION; THREE DIMENSIONAL;

ARTERY; LASER SCANNING CONFOCAL MICROSCOPY; THRESHOLDING;

MICROSCOPIC EXAMINATION;

EID: 0032226597     PISSN: 10407286     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1023482003483     Document Type: Article

References (40)

1. Ahuja, N. (1996). A transform for multiscale image segmentation by integrated edge and region detection. IEEE Trans. Pattern Analy. Machine Intell. 18: 1211-1235.
2. Arribas, S., Daly, C., and McGrath, J. C. (1999). Measurement of vascular remodelling by confocal microscopy. Methods Enzymol. (Suppl. Confocal Microscopy) 307: 246-273.
3. Arribas, S. M., Hillier, C., Gonzalez, C., McGroy, S., Dominiczak, A. F., and McGrath, J. C. (1997). Cellular aspects of vascular remodelling in hypertension revealed by confocal microscopy. Hypertension 30: 1455-1464.
4. Chang, J. S., Liao, H. Y. M., Hor, M. K., Hsieh, J. W., and Chern, M. Y. (1997). New automatic multi-level thresholding technique for segmentation of thermal images. Image Vision Comput. 15: 23-34.
5. Chang, F. J., Yen, J. C., and Chang, S. (1995). A new criterion for automatic multilevel thresholding. IEEE Trans. Image Process 4: 370-378.
6. Chen, L. H., and Lin, W. C. (1997). Visual surface segmentation from stereo. Image and Vision Computing 15: 95-106.
7. Coleman, G., and Andrews, H. C. (1979). Image segmentation and clustering. Proceedings of IEEE, pp. 773-785.
8. Daly, C. J., Gordon, J. F., and McGrath, J. C. (1991). Fluorescence image analysis methods for the study of smooth music cell interaction within the wall of small blood vessels. In Mulvany, M. J. et al. (eds.), Resistance Arteries, Structure and Function. Amsterdam, Elsevier Science Publishers, pp. 339-343.
9. Daly, C. J., Gordon, J. F., and McGrath, J. C. (1992). The use of fluorescent nuclear dyes for the study of blood vessel structure and function: novel applications of existing techniques. J. Vasc. Res. 29: 41-48.
10. Daly, C. J., Gordon, J. F., and McGrath, J. C. (1994). The use of confocal microscopy for the study of resitance artery structure and function. J. Vasc. Res. 31(Suppl. 1): 018.
11. Elliot, P. J., Diedrichsen, J., Goodson, K. J., Ristesmith, R., and Sivewright, G. J. (1996). An object-oriented system for 3D medical image-analysis. IBM Systems J. 35: 4-24.
12. Fu, Y. S., Ferency, A., Huang, I., and Gelfand, M. M. (1988). Digital imaging analysis of normal hyperplastic and malignant endometrical cells in endometrial brushing samples. Analyt. Quantit. Cytol. Histol. 2: 139.
13. Haralick, R. (1983). Image segmentation survey. In Fangeras, O. (ed.), Fundementals in Computer Vision, Cambridge University Press, Cambridge, New York, pp. 209-224.
14. Hertz, L., and Shafer R. W. (1988). Multilevel thresholding using edge matching. Comput. Vision Graphics Image Process 44: 279-295.
15. Hoover, A., Baptiste, G. J., Jiang, X., Flynn, P. J., Bunke, H., Goldgof, D. B., Bowyer, K., Eggert, D. W., Fitzgibbon, A., and Fisher, R. B. (1996). An experimental comparison of range image segmentation algorithms. IEEE Trans. Pattern Anal. Machine Intell. 18: 673-689.
16. Jain, A. K., Zhong, Y., and Lakshmanan, S. (1996). Object matching using deformable templates. IEEE Trans. Pattern Anal. Machine Intell. 18: 267-278.
17. Johnston, B., Atkins, M. S., Mackiewich, B., and Anderson, M. (1996). Segmentation of multiple sclerosis lesions in intensity corrected multispectral MRI. IEEE Trans. Medical Imaging 15: 154-169.
18. Jordan, S. W., Brayer, J. M., Bartels, P. H., and Anderson, R. E. (1988). Video-based image collection for quantitative histopathology. Anayt. Quantit. Cytol. Histol. 1: 37.
19. Kurita, T. (1995). An efficient clustering-algorithm for region merging. IEICA Trans. Inform. Systems E78D (12): 1546-1551.
20. Kwok, S. H., and Constantinides. A. G. (1997). A fast recursive shortest spanning tree for image segmentation and edge detection. IEEE Trans. Image Processing 6: 328-332.
21. Lee, C. K., and Wong, S. P. (1996). A mathematical morphologicla approach for segmenting heavily noise-corrupted images. Pattern Recognition 29: 1347-1358.
22. Luo, D. (1995). Image processing and pattern recognition applied to soil structures. Ph.D. thesis, University of Glasgow, UK.
23. Luo, D., and Ma. D. (1989). Bi-boundary-line method for curve-enclosed area calculation. J. Sichuan University (Natural Science Edition) 26: 58-65.
24. Luo, D., Macleod, J. E. S., Leng, X., and Smart, P. (1992). Automatic orientation analysis of particles of soil microstructures. Geotechnique 42: 97-107.
25. McGrath, J. C., Arribas, S. M., Daly, C. J., Gordon, J. F. (1995). Confocal microscopy for structure and real-time pharmacology in blood vessels. J. Human Hypertens. 9: 645-647.
26. Nguyen, N. G., Poulsen, R. S., and Louis, C. (1983). Some new colour features and theire application to cervical cell classification. Pattern Recognition 4: 401.
27. Ohlander, R., Price, K., and Redds, R. (1978). Picture segmentation by a recursive region spliting method. Comput. Graphics Image Process. 8: 313-333.
28. Ong, S. H., Jin, X. C., Jayassooriah, and Sinniah, R. (1996). Image analysis of tissue section. Computers Biol. Med. 26: 269-279.
29. Paramarkos, N., and Gatos, B. (1994). A new approach for multi-level threshold selection. Graphic Models Image Process 56: 357-3701.
30. Pawley, J. B. (1995). Handbook of Biological Confocal Microscopy (2nd ed.), Plenum Press, London.
31. Porter, R., and Canagarajah, N. (1996). A robust automatic clustering scheme for image segmentation using wavelets. IEEE Trans. Image Processing 5: 662-665.
32. Postaire, J. G., and Amezian, M (1992). A pattern classification approach to multilevel thresholding for image segmentation. In Shapiro, L., and Rosenfeld, A. (eds.), Computer Vision and Image Processing, pp. 307-328.
33. Ridler, T. W., and Calvard, S. (1978). Picture thresholding using iterating selection method. IEEE Trans. Systems Man Cybernet 8: 630-632.
34. Shirvaikar, M. V., and Trivedi, M. M. (1995). Texture segmentation-an unsupervised approach. Int. J. Uncertainty Fuzziness and Knowledge-Based Systems 3: 431-449.
35. Singleton, H. R., and Pohost, G. M. (1997). Automatic cardica MR image segmentation using edge detection by tissue classification in pixel neighborhoods. Magn. Reson. Med. 37: 418-424.
36. Strasters, K. C., and Gerbrands, J. J. (1991). Three-dimensional image segmentation using a split merge, and group approach. Pattern Recognition Letter 12: 307-325.
37. Wells, W. M. Grimson, W. E. L., Kikinis, R., and Jolesz, F. A. (1996). Adaptive segmentation of MRI data. IEEEE Trans. Medical Imaging 15: 429-442.
38. Wu, H. S., Barba, J., and Gil, J. (1996). Morphological segmentation of textured images. J. Imaging Sci. Technol. 40: 265-270.
39. Young, T. Y., and Fu, K. S. (1986). Handbook of Pattern Recognition and Image Processing. Academic Press, New York.
40. Zhu, S. C., and Yuille, A. (1996). Region competition-unifying snakes, region growing, and Bayes MDL for multiband image segmentation. IEEE Trans. Pattern Anal. Machine Intell. 18: 884-900.