Segmentation of nucleus and cytoplasm of white blood cells using Gram-Schmidt orthogonalization and deformable models

International Conference on Signal Processing Proceedings, ICSP

Volumn , Issue , 2008, Pages 801-805

  Rezatofighi, S H ^a   Zoroofi, R A ^a   Sharifian, R ^b   Soltanian Zadeh, H ^a,c  

^a UNIVERSITY OF TEHRAN   (Iran)

^b TEHRAN UNIVERSITY OF MEDICAL SCIENCES   (Iran)

^c HENRY FORD HOSPITAL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC RECOGNITION; DEFORMABLE MODELS; FEATURE EXTRACTION AND CLASSIFICATION; GRAM-SCHMIDT; GRAM-SCHMIDT ORTHOGONALIZATION; INITIAL CONTOUR; MANUAL SEGMENTATION; NOVEL METHODS; PRE-PROCESSING METHOD; WHITE BLOOD CELLS;

CELL MEMBRANES; CYTOLOGY; DEFORMATION; FEATURE EXTRACTION; IMAGE SEGMENTATION; SIGNAL PROCESSING;

BLOOD;

EID: 67249145612     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICOSP.2008.4697250     Document Type: Conference Paper

References (14)

1. J. WU, P. Zeng, Y. Zhou, and C. Oliver, "A Novel Color Image Segmentation Method and Its Application to White Blood Cell Image Analysis", International Conference on Signal Processing, vol. 2, Beijing, November 2006, pp. 245-248.
2. H. Hengen, S. L. Spoor, and M. C. Pandit, "Analysis of Blood and Bone Marrow Smears Using Digital Image Processing Techniques", in: M. Sonka, J. M. Fitzpatrick, (Eds.), Proceedings of the SPIE, Medical Imaging 2002: Image Processing, vol. 4684, 2002, pp. 624-635.
3. I. Cseke, "A Fast Segmentation Scheme for WBC Images", IEEE Conf. Image, Speech and Signal Analysis, 1992, pp. 530-533.
4. S. F. Bikhet, A. M. Darwish, H. A. Tolba, and S. I. Shaheen, "Segmentation and Clustering of WBC", IEEE Conf. Acoustics, Speech, and Signal Processing, vol. 4, 2000, pp. 2259-2261.
5. Q. Liano and Y. Deng, "An Accurate Segmentation Method for White Blood Cell Images", IEEE Conf. Biomedical Imaging, 2002, pp. 245-248.
6. N. T. Umpon, "Patch-based White Blood Cell Nucleus Segmentation Using Fuzzy Clustering", ECTI Trans. Electrical. Electronic. Communications, vol. 3, no. 1, 2005, pp. 5-10.
7. N. Guo, L. Zeng, and Q. Wu, "A Method Based on Multi-spectral Imaging Technique for White Blood Cell Segmentation", Computers in Biology and Medicine, vol. 37, 2006, pp. 70-76.
8. J. M. chassery and C. Garbay, "An Iterative Segmentation Method Based on Contextual Color and Shape Criterion", IEEE Trans. Pattern Anal. Machine Intell., vol. 6, no. 6, 1984, pp. 795-800.
9. K. Jiang, Q. M. Liao, and S. Y. Dai, "A Novel White Blood Cell Segmentation Scheme Using Scale-space Filtering and Watershed Clustering", Proceedings of the Second International Conference on Machine Learning and Cybernetics, 2003, pp. 2820-2825.
10. th International Conference on Signal Processing, vol. 2, Beijng, 2006, pp. -.
11. Guyton, C. and E. Hall, Text Book of Medical Physiology, Elsevier Saunders, Pennsylvania USA, 2006.
12. H. Soltanian-Zadeh, D. J. Peck, and D. O. Hearshen, and Renee R. Lajiness-O'Neill: "Model-Independent Method for fMRI Analysis." IEEE Trans. Med. Imag., vol. 23, no. 3, March 2004, pp. 285-296.
13. M. Kass, A. Witkin, and D. Terzopoulos, "Snakes: Active Contour Models," Int. J. Comp. Vision, vol. 1, no. 4, 1987, pp. 321-331.
14. C. C. H. Lean, A. K. B. See, S. A. Shanmugam, "An Enhanced Method for the Snake Algorithm", International Conference on Innovative Computing, Information and Control (ICICIC'06), vol. 1, no. 30, August 2006, pp. 240-243.