Extraction of karyocytes and their components from microscopic bone marrow images based on regional color features

Pattern Recognition

Volumn 37, Issue 2, 2004, Pages 351-361

  Zhang, Xi Wen ^a   Song, Ji Qiang ^b   Lyu, Michael R ^b   Cai, Shi Jie ^a  

^a NANJING UNIVERSITY   (China)

^b CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Feature block growing; Image segmentation; Karyocyte extraction; Microscopic bone marrow image; Regional color features

Indexed keywords

COLOR IMAGE PROCESSING; COMPUTER AIDED DESIGN; MEDICAL IMAGING;

PIXELS;

PATTERN RECOGNITION;

IMAGE ANALYSIS;

EID: 0242539891     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2003.07.007     Document Type: Article

References (19)

1. P. Sobrevilla, E. Montseny, J. Keller, White blood karyocyte detection in bone marrow images, in: Proceedings of the 18th International Conference of the North American Fuzzy Information Processing Society, New York, USA, June 10-12, 1999, pp. 403-407.
2. Beutler E. Lichtman M.A. Coller B.S. Kipps T.J. URI Seligsohn, Williams Hematology 6th Edition 2001 McGraw-Hill Publishing Company USA, New York
3. F. van der Heijden, Image based measurement systems, Object Recognition and Parameter Estimation, Wiley, West Sussex, England, 1995, pp. 215.
4. Cong G. Parvin B. Model-based segmentation of nuclei Pattern Recognition 33 8 2000 1383-1393
5. Yang F. Jiang T. Karyocyte image segmentation with kernel-based dynamic clustering and an ellipsoidal karyocyte shape model J. Biomed. Informatics 34 2 2001 67-73
6. Garrido A. de la Blanca N.P. Applying deformable templates for cell image segmentation Pattern Recognition 33 5 2000 821-832
7. Horowitz S.L. Pavilidis T. Picture segmentation by a tree traversal algorithm J. Assoc. Comput. Mach. 23 2 1976 368-388
8. Wu X. Adaptive split-and-merge segmentation based on piecewise least-square approximation IEEE Trans. Pattern Anal. Mach. Intell. 15 8 1993 808-815
9. Adams R. Bischof L. Seeded region growing IEEE Trans. Pattern Anal. Mach. Intell. 16 6 1994 641-647
10. Mehnert A. Jackway P. An improved seeded region growing algorithm Pattern Recognition Lett. 18 10 1997 1065-1071
11. Aus H.M. Harms H. ter Meulen V. Gunzer U. Statistical evaluation of computer extracted blood karyocyte features for screening populations to detect leukemias Devjver P.A. Kittler J. Pattern Recognition Theory and Applications 1987 Springer Berlin, Heidelberg
12. Park J. Keller J.M. Snakes on the watershed IEEE Trans. Pattern Anal. Mach. Intell. 23 10 2001 1201-1205
13. Pascal Christopher Bamford, Segmentation of cell images with application to cervical cancer screening, a dissertation, University of Queensland, 1999, pp. 52-53.
14. Cheng H.D. Jiang X.H. Sun Y. Wang J. Color image segmentation: advances and prospects Pattern Recognition 34 12 2001 2259-2281
15. Zhang Y.J. A survey on evaluation methods for image segmentation Pattern Recognition 29 8 1996 1335-1346
16. Zhang Y.J. Evaluation and comparison of different segmentation algorithms Pattern Recognition Lett. 18 10 1997 963-974
17. Lee S.U. Chung S.Y. Park R.H. A comparative performance study of several global thresholding techniques for segmentation Comput. Vision Graphics Image Process. 52 2 1990 171-190
18. Ostu N. A threshold selection method from gray-level histogram IEEE Trans. Syst. Man Cybern. 9 1 1979 62-66
19. Canny J. A computational approach to edge detection IEEE Trans. Pattern Anal. Mach. Intell. 8 6 1986 679-698