Dealing with multiple types of expert knowledge in medical image segmentation: A rough sets style approach

IEEE International Conference on Fuzzy Systems

Volumn 2, Issue , 2002, Pages 884-889

  Hirano, Shoji ^a   Sun, Xiaoguang ^a   Tsumoto, Shusaku ^a  

^a SHIMANE UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

MEDICAL IMAGE SEGMENTATION; REGIONS OF INTERESTS;

CARDIOVASCULAR SYSTEM; DATA MINING; IMAGE ANALYSIS; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGING; ROUGH SET THEORY;

IMAGE SEGMENTATION;

EID: 0036456264     PISSN: 10987584     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (4)

1. Z. Pawlak, Rough Sets, Theoretical Aspects of Reasoning about Data, Kluwer Academic Publishers, Dordrecht, 1991.
2. S. Tsumoto, "Automated Discovery of Positive and Negative Knowledge in Clinical Databases," IEEE Engineering in Medicine and Biology Magazine, vol. 19, no. 4, pp. 56-62, 2000.
3. J. W. Grzymala-Busse, "LERS - A System for Learning from Examples Based on Rough Sets," in R. Slowinski (Ed.) Intelligent Decision Support. Handbook of Applications an Advances of the Rough Set Theory, Kluwer Academic Publishers, Dordrecht, 1992.
4. N. H. Son, A. Skowron, and M. Szczuka, "Analysis of Image Sequences for the Unmanned Aerial Vehicle," in Proceedings of International Workshop on Rough Set Theory and Granular Computing 2001, pp. 185-188, 2001.