Clustered nuclei splitting using curvature information

Proceedings - 2011 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2011

Volumn , Issue , 2011, Pages 352-357

  Zhang, Chao ^a,b   Sun, Changming ^b   Pham, Tuan D ^a  

^a UNIVERSITY OF NEW SOUTH WALES   (Australia)

^b CSIRO   (Australia)

Author keywords

Clustered cell nuclei; Curvature information; Image segmentation; Watershed segmentation

Indexed keywords

CELL NUCLEUS; CURVATURE INFORMATION; DISTANCE MAP; IMAGE SEGMENTATION ALGORITHM; REAL IMAGES; SEGMENTATION METHODS; TISSUE SECTIONS; WATERSHED SEGMENTATION;

ALGORITHMS; TISSUE;

IMAGE SEGMENTATION;

EID: 84863052510     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/DICTA.2011.66     Document Type: Conference Paper

References (17)

1. R. Adams and L. Bischof. Seeded region growing. IEEE Transactions on Pattern Analysis and Machine Intelligence, 16(6):641-647, June 1994.
2. D. Baggett, M. Nakaya, M. McAuliffe, T. P. Yamaguchi, and S. Lockett. Whole cell segmentation in solid tissue sections. Cytometry Part A, 67A(2):137-143, September 2005. (Pubitemid 41437530)
3. X. Bai, C. Sun, and F. Zhou. Splitting touching cells based on concave points and ellipse fitting. Pattern Recognition, 42(11):2434-2446, November 2009.
4. J. Canny. A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-8(6):679-698, November 1986.
5. J. Cheng and J. C. Rajapakse. Segmentation of clustered nuclei with shape markers and marking function. IEEE Transactions on Biomedical Engineering, 56(3):741-748, March 2009.
6. L. Cohen. Note on active contour models and balloons. CVGIP: Image Understanding, 53(2):211-218, March 1991.
7. L. Cohen and I. Cohen. Finite-element methods for active contour models and balloons for 2-D and 3-D images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(11):1131-1147, November 1993.
8. M. Kass, A. Witkin, and D. Terzopoulos. Snakes: Active contour models. International Journal of Computer Vision, 1(4):321-331, January 1988.
9. D. McCullough, P. Gudla, B. Harris, J. Collins, K. Meaburn, M.-A. Nakaya, T. Yamaguchi, T. Misteli, and S. Lockett. Segmentation of whole cells and cell nuclei from 3-D optical microscope images using dynamic programming. IEEE Transactions on Medical Imaging, 27(5):723 -734, May 2008.
10. S. Osher and R. P. Fedkiw. Level set methods: An overview and some recent results. Journal of Computational Physics, 169(2):463-502, May 2001. (Pubitemid 33665457)
11. T. Srinark and C. Kambhamettu. A framework for multiple snakes and its applications. Pattern Recognition, 39(9):1555-1565, September 2006. (Pubitemid 43867569)
12. H. Talbot. Elliptical distance transforms and applications. In Discrete Geometry for Computer Imagery, pages 320-330. Springer, 2006.
13. H. Talbot and B. Appleton. Elliptical distance transforms and the object splitting problem. In Proceedings of the VIth International Symposium on Mathematical Morphology: Sydney, 3-5 April, 2002, pages 229-240. CSIRO.
14. W. Tao, F. Chang, L. Liu, H. Jin, and T. Wang. Interactively multiphase image segmentation based on variational formulation and graph cuts. Pattern Recognition, 43(10):3208-3218, October 2010.
15. L. Vincent and P. Soille. Watersheds in digital spaces: An efficient algorithm based on immersion simulations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(6):583-598, June 1991. (Pubitemid 21675616)
16. C. Zhang, C. Sun, T. D. Pham, P. Vallotton, and M. Fenech. Detection of nuclear buds based on ellipse fitting. In Digital Image Computing: Techniques and Applications, pages 178-183, Sydney, Australia, 2010. IEEE Computer Society.
17. S. W. Zucker. Region growing: Childhood and adolescence. Computer Graphics and Image Processing, 5(3):382-399, September 1976.