Extended discounting scheme for evidential reasoning as applied to MS lesion detection

Proceedings of the Seventh International Conference on Information Fusion, FUSION 2004

Volumn 1, Issue , 2004, Pages 280-287

  Zhu, Hongwei ^a   Basir, Otman ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Adapi live fuzzy evidential reasoning; Brain tissue segmentation; Dempster Shafer evidence theory; Discounting; MS detection

Indexed keywords

BRAIN; DATABASE SYSTEMS; FUZZY SETS; IMAGE ANALYSIS; MAGNETIC RESONANCE IMAGING; TISSUE;

BRAIN TISSUE DETECTION; CEREBROSPINAL FLUIDS; DATA SETS; LESION DETECTION;

IMAGE SEGMENTATION;

EID: 6344287552     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. K. Van Leemput, F. Maes, D. Vandermeulen, A. Colchester, and P. Suetens. Automated segmentation of multiple sclerosis lesions by model outlier detection. IEEE Trans. Medical Imaging, 20:677-688, 2001.
2. D. Goldberg-Zimring, A. Achiron, and S. Miron. Automated detection and characterization of multiple sclerosis lesions in brain MR images. Magnetic Resonance Imaging, 16: 311-318, 1998.
3. Y. Hata, S. Kobashi, and S. Hirano. Automated segmentation of human brain MR images aided by fuzzy information granulation and fuzzy inference. IEEE Trans. SMC, Part C, 30: 381-395, 2000.
4. T.W. Kim and C.H. Paik. Unsupervised statistical adaptive segmentation of brain MR images using the MDL principle. In Proc. 20th Annual Int. Conf. of the IEEE, 2: 617-620, 1998.
5. H. Zhu and O. Basir. Fuzzy evidential reasoning applied to multi-modality MR brain image segmentation with source selection. In Proc. 7th Joint Conf. Info. Sci., 2003.
6. S.A. Hojjatoleslami, F. Kruggel, and D.Y. von Cramon. Segmentation of white matter lesions from volumetric MR images. Medical Image Computing and Computer-Assisted Intervention - MICCAI'99, pages 52-61, 1999.
7. H. Zhu and O. Basir. Adaptive fuzzy evidential reasoning for automated brain tissue segmentation. In Proc. 7th Int. Conf. Information Fusion, Stockholm, Sweden, 2004.
8. K.R. Maravilla. Multiple sclerosis. In D.D. Stark, W.G. Bradley, editors, Magnetic Resonance Imaging, St. Louis, MO: Mosby, pages 344-358, 1988.
9. M. Kamber, R. Shanghai, D.L. Collins, G.S. Francis, and A.C. Evans. Model-based 3-D segmentation of multiple sclerosis lesions in magnetic resonance brain images. IEEE Trans. Medical Imaging, 14: 442-453, 1995.
10. G. Shafer, A Mathematical Theory of Evidence, Princeton University Press, Princeton, NJ, 1976.
11. D.L. Collins, A.P. Zrjdenbos, V. Kollokian, J.G. Sled, N.J. Kabani, C.J. Holmes, and A.C. Evans. Design and construction of a realistic digital brain phantom. IEEE Trans. Medical Imaging, 17: 463-468, 1998.
12. P. Smets. Data fusion in transferable belief model. In Proc. 3rd Int. Conf. Information Fusion, pages 21-33, 2000.
13. J.W. Guan and D.A. Bell. Approximate reasoning and evidence theory. Information Sciences, 96:207-235, 1997.
14. S. Fahre, X. Briottet, and A. Appriou. Impact of contextual information integration on pixel fusion. IEEE Trans. Geosci. Remote Sensing, 40: 1997-2010, 2001.
15. H. Zhu and O. Basir. A scheme for constructing evidence structures in Dempster-Shafer evidence theory for data fusion. In Proc. 5th IEEE Int. Symposium on Computational Intelligence in Robotics and Automation, pages 16-20, 2003.
16. D. Dubois and H. Prade. On several representations of an uncertainty body of evidence. In M. M. Gupta, E. Sanchz, editors, Fuzzy Informaton and Decision Processes, pages 167-181, North-Holland, New-York, 1982.
17. A.P. Zijdenbos, B.M. Dawant, R.A. Margolin, and A.C. Palmer. Morphometric analysis of white matter lesions in MR images: method and validation. IEEE Trans. Medical Imaging, 13: 716-724, 1994.
18. J.J. Bartko. Measurement and reliability: statistical thinking considerations, Schizophrenia Bullet., 17:483-489, 1991.