Bleeding Detection from Capsule Endoscopy Videos

Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"

Volumn , Issue , 2008, Pages 4780-4783

  Giritharan, Balathasan ^a   Yuan, Xiaohui ^a   Liu, Jianguo ^a   Buckles, Bill ^a   Oh, JungHwan ^a   Tang, Shou Jiang ^b  

^a UNIVERSITY OF NORTH TEXAS   (United States)

^b UNIVERSITY OF TEXAS SOUTHWESTERN MEDICAL CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ENDOSCOPY; SUPPORT VECTOR MACHINES;

BLEEDING DETECTIONS; CAPSULE ENDOSCOPY; CLASSIFICATION METHODS; IMAGE FEATURES; IMBALANCED DATA-SETS; LEARNING PROCESS; LOW SENSITIVITY; TRAINING SAMPLE;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BLEEDING; CAPSULE ENDOSCOPY; CLUSTER ANALYSIS; COMPUTER ANALYSIS; COMPUTER PROGRAM; HUMAN; IMAGE PROCESSING; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; VIDEORECORDING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CAPSULE ENDOSCOPY; CLUSTER ANALYSIS; COMPUTING METHODOLOGIES; HEMORRHAGE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SOFTWARE; VIDEO RECORDING;

EID: 61849137267     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/iembs.2008.4650282     Document Type: Conference Paper

References (14)

1. D. G. Adler and C. J. Gostout. Wireless capsule endoscopy. Hospital Physician, 39(5):14-22, 2003.
2. R. Barandela, J. S. Sanchez, V. Garcia, and F. J. Ferri. Learning from imbalanced sets through resampling and weighting. In Lecture Notes in Computer Science, volume 2652, pages 80-88, 2003.
3. L. Breiman. Bagging predictors. Machine Learning, 24(2): 123-140, August 1996.
4. N. V. Chawla, K. W. Bowyer, L. O. Hall, and P. Kegelmeyer. Smote: Synthetic minority over-sampling technique. Journal of Artificial Intelligence and Research, 16:321-357, 2002.
5. M. T. Coimbra and J.P. S. Cunha. Mpeg-7 visual descriptorscontributions for automated feature extraction in capsule endoscopy. Circuits and Systems for Video Technology, IEEE Transactions on, 16(5):628-637, May 2006.
6. Y M Huang and S Du. Weighted support vector machine for classification with uneven training class sizes. Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on, 7:4365-4369 Vol. 7, 18-21 Aug. 2005.
7. N. Japkowicz. Class imbalance: Are we focusing on the right issue? In ICML-KDD'2003 Workshop, Washington, DC, August 2003.
8. V. S. Kodogiannis and M. Boulougoura. An adaptive neurofuzzy approach for the diagnosis in wireless capsule endoscopy imaging. International Journal of Information Technology, 13(1):46-54, 2007.
9. G. D. Magoulas, V. P. Plagianakos, D. K. Tasoulis, and M. N. Vrahatis. Tumor detection in colonoscopy using the unsupervised k-windos clustering algorithm and neural netowrks. In Proceeding of 4th European Symposium on Biomedical Engineering, Patras, Greece, June 2004.
10. B. S. Manjunath, J.-R. Ohm, V. V. Vasudevan, and A. Yamada. Color and texture descriptors. Circuits and Systems for Video Technology, IEEE Transactions on, 11(6):703-715, Jun 2001.
11. B. Raskutti and A. Kowalczyk. Extreme re-balancing for svms: a case study. SIGKDD Explor. Newsl., 6(1):60-69, 2004.
12. V. Vapnik. The Nature of Statistical Learning Theory. Springer, New York, 1999.
13. F. Vilarino, L. I. Kuncheva, and P. Radeva. ROC curves and video analysis optimization in intestinal capsule endoscopy. Pattern Recognition Letters, 27:875-881, 2006.
14. F. Vilarino, G. Lacey, J. Zhou, H. Mulcahy, and S. Patchett. Automatic labeling of colonoscopy video for cancer detection. Lecture Notes in Computer Science: Pattern Recognition and Image Analysis, 4477:290-297, July 2007.