Automatic classification of images with appendiceal orifice in colonoscopy videos

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

Volumn , Issue , 2006, Pages 2349-2352

  Cao, Yu ^a   Liu, Danyu ^a   Tavanapong, Wallapak ^a   Wong, Johnny ^a   Oh, JungHwan ^b   De Groen, Piet C ^c  

^a Iowa State University   (United States)

^b Center for Advanced Research and Technology   (United States)

^c Mayo Clinic   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BIOMEDICAL ENGINEERING; CONTENT BASED RETRIEVAL; ENDOSCOPY; MEDICAL IMAGING;

COLONOSCOPY VIDEOS; HUMAN COLON; VIDEO FRAMES;

IMAGE PROCESSING;

ALGORITHM; APPENDIX; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CAPSULE ENDOSCOPY; COLON; COMPUTER ASSISTED DIAGNOSIS; EVALUATION STUDY; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; APPENDIX; ARTIFICIAL INTELLIGENCE; CAPSULE ENDOSCOPY; COLON; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 34047166595     PISSN: 05891019     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEMBS.2006.260686     Document Type: Conference Paper

References (14)

1. American Cancer Society, "Colorectal Cancer Facts & Figures," American Cancer Society, 2005.
2. D. Lieberman (Editorial), "Quality and Colonoscopy: a New Imperative," Gastrointestinal Endoscopy, vol. 61, no. 3, pp. 392-394, 2005.
3. Y. Cao, D. Liu, W. Tavanapong, J.-H. Oh, J. Wong, and P.C. de Groen, "Computer-aided Detection of Biopsy and Therapeutic Operations in Colonoscopy Videos," Submitted to IEEE Trans. on Biomedical Engineering.
4. S. Hwang, J. Oh, J. Lee, Y. Cao, W. Tavanapong, D. Liu, J. Wong, and P.C. de Groen, "Automatic Measurement of Quality Metrics for Colonoscopy Videos," Proc. of ACM Multimedia, Singapore, 2005, pp. 912-921.
5. D. Lowe, "Distinctive Image Features from Scale-Invariant Keypoints," Int'l Journal of Computer Vision, vol. 60, no. 2, pp. 91-110, 2004.
6. S. J. Phee and W. S. Ng, "Automatic of colonoscopy: Visual control aspects," in IEEE Eng. in Medicine and Biology Magazine, vol. 17, Issue 3, pp. 81-88, 1998.
7. N. O. Khessal and T. M. Hwa, "The Development of an Automatic Robotic Colonoscope," Proc. of TENCON, 2000, vol. 2, pp. 71-76, 2000.
8. N. Esgiar, R. N. G. Naguib, B. S. Sharif, M. K. Bennett, and A. Murray, "Microscopic Image Analysis for Quantitative Measurement and Feature Identification of Normal and Cancerous Colonic Mucosa," IEEE Trans Info Tech. Biomed, vol. 2, no. 3, pp. 197-203, 1998.
9. S. A. Karkanis, D. K. lakovidis, D. E. Maroulis, D. A. Karras, and M. Tzivras, "Computer-Aided Tumor Detection in Endoscopic Video Using Color Wavelet Features," IEEE Trans. on Information Technology in Biomedicine, vol. 7, no. 3, pp. 141-152, 2003.
10. G. D. Magoulas, V. P. Plagianakos, D. K. Tasoulis, and M. N. Vrahatis, "Tumor Detection in Colonoscopy using the Unsupervised K-windows Clustering Algorithm and Neural Networks," Proc. of European Symposium on Biomedical Engineering, Patras, Greece, 2004.
11. A. Kaufman, S. Lakare, I. Bitter, and K. Kreeger, "Virtual Colonoscopy," in Communications of the ACM, vol. 48, pp. 37-41, 2005.
12. R. Fergus, P. Perona, and A. Zisserman, "Object class recognition by unsupervised scale-invariant learning," Proc. of Computer Vision and Pattern Recognition, Madison, WI, 2003, pp. 264-271.
13. Y. Deng and B. S. Manjunath, "Unsupervised segmentation of color-texture regions in images and video," IEEE Trans. on Pattern Analysts and Machine Intelligence, vol. 23, pp. 800-810, 2001.
14. P. K. L. Xu and E. Oja, "A new curve detection method: Randomized hough transform," Pattern Recognition Letters, vol. 11, pp. 331-338, 1990.