Multi-class multi-instance learning for lung cancer image classification based on bag feature selection

Proceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008

Volumn 2, Issue , 2008, Pages 487-492

  Zhu, Liang ^a   Zhao, Bo ^a   Gao, Yang ^a  

^a NANJING UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL ORGANS; FEATURE EXTRACTION; FUZZY LOGIC; FUZZY SYSTEMS; IMAGE ANALYSIS; IMAGE CLASSIFICATION;

EFFECTIVE SOLUTIONS; FEATURE SELECTIONS; FEATURE SPACES; HAUSDORFF DISTANCES; LEARNING PROBLEMS; LUNG CANCER CELLS; LUNG CANCERS; SINGLE CELLS; SUPERVISED LEARNING METHODS;

IMAGE PROCESSING;

EID: 58049191074     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FSKD.2008.54     Document Type: Conference Paper

References (13)

1. Y. Chen, J. Bi, and J.Wang. Miles: Multiple-instance learning via embedded instance selection. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2006.
2. Y. Chen and J. Wang. Image categorization by learning and reasoning with regions. Journal of Machine Learning Research (JMLR), 5:913-939, Feb 2004.
3. T. Dietterich, R. Lathrop, and T. Lozano-Pérez. Solving the multiple-instance problem with axis-parallel rectangles. Artificial Intelligence, 89(1-2):31-71, 1997.
4. Y. Freund and R. E. Schapire. A decision-theoretic generalization of online learning and an application to boosting. Journal of Computer and System Sciences, 55(1):119-139, August 1997.
5. P. Huang, S. Zong, and C. L. Tan. Chart image classification using multiple-instance learning. Proceedings of the Eighth IEEE Workshop on Applications of Computer Vision, Feb 2007.
6. X. Huang, S.-C. Chen, and M.-L. Shyu. An open multiple instance learning framework and its application in drug activity prediction problems. Proceedings of the 3rd IEEE Symposium on BioInformatics and BioEngineering, Mar 2003.
7. D. P. Huttenlocher, G. A. Klanderman, and W. J. Rucklidge. Comparing images using the hausdorff distance. IEEE Transactions on PAMI, 15(9):850 863, 1993.
8. O. Maron and Lozano-Pérez. A framework for multiple-instance learning. In Advances in Neural Information Processing Systems, 10:570-576, 1998.
9. N. OSTU. A threshold selection method from gray-level histogram. IEEE Trans. SMC, 9(1):62-69, 1979.
10. G. Ruffo. Learning single and multiple instance decision trees for computer security applications. PhD dissertation, Department of Computer Science, University of Turin, Torino, Feb 2000.
11. R. Schapire and Y. Singer. Improved boosting algorithms using confidence-rated predictions. Machine Learning, 37(3):297-336, 1999.
12. Z.-H. Zhou and M.-L. Zhang. Solving multi-instance problems with classifier ensemble based on constructive clustering. Knowledge and Information Systems, 2007.
13. Z.-H. Zhou, M.-L. Zhang, and K.-J. Chen. A novel bag generator for image database retrieval with multi-instance learning techniques. Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence, Nov 2003.