Informative frame classification for endoscopy video

Medical Image Analysis

Volumn 11, Issue 2, 2007, Pages 110-127

  Oh, JungHwan ^a   Hwang, Sae ^b   Lee, JeongKyu ^b   Tavanapong, Wallapak ^c   Wong, Johnny ^c   de Groen, Piet C ^d  

^a UNIVERSITY OF NORTH TEXAS   (United States)

^b University of Texas at Arlington   (United States)

^c Iowa State University   (United States)

^d Mayo Clinic College of Medicine   (United States)

Author keywords

Clustering; Colonoscopy; Endoscopy; Frame classification; Specular reflection detection; Texture

Indexed keywords

CLASSIFICATION (OF INFORMATION); CLUSTERING ALGORITHMS; COMPUTER AIDED DIAGNOSIS; FOCUSING; MEDICAL IMAGING; REFLECTION;

COLONOSCOPY; FRAME CLASSIFICATION; SPECULAR REFLECTION DETECTION;

ENDOSCOPY;

ARTICLE; CALCULATION; CLASSIFICATION; CLUSTER ANALYSIS; COLONOSCOPY; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC IMAGING; ENDOSCOPY; FOURIER TRANSFORMATION; IMAGE ANALYSIS; IMAGE DISPLAY; IMAGE QUALITY; IMAGE RECONSTRUCTION; INTERMETHOD COMPARISON; PREDICTION; PRIORITY JOURNAL; SENSITIVITY AND SPECIFICITY; VIDEORECORDING;

DIAGNOSIS, COMPUTER-ASSISTED; ENDOSCOPY; FOURIER ANALYSIS; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; SENSITIVITY AND SPECIFICITY; VIDEO RECORDING;

EID: 33847631274     PISSN: 13618415     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.media.2006.10.003     Document Type: Article

References (46)

1. Ayers G., and Dainty J. Iterative blind Deconvolution method and its applications. Optics Letters 13 7 (1988) 547-549
2. Bates R., and Jiang H. Deconvolution - recovering the seemingly irrecoverable!. International Trends in Optics (1991) 423-437
3. Beach, J., 2002. Spectral reflectance technique for retinal blood oxygen evaluation in humans. In: Proceedings of the Applied Imagery Pattern Recognition Workshop, October, pp. 117-123.
4. Bevk, M., Kononenko, I., 2002. A statistical approach to texture description of medical images: a preliminary study. In: Proceedings of the IEEE Symposium on Computer-Based Medical Systems, June, pp. 239-244.
5. Bhangale, T., Desai, U., Sharma, U., 2000. An unsupervised scheme for detection of microcalcifications on mammograms. In: Proceedings of the International Conference on Image Processing, pp. 184-187.
6. Canny J. A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 8 6 (1986)
7. Carson C., Belongie S., Greenspan H., and Malik J. Blobworld: image segmentation using expectation maximisation and its application to image querying. IEEE Transactions on Pattern Analysis and Machine Intelligence 24 (2002) 1026-1038
8. C.D.S., L.Z.K., 2003. A novel approach to detect and correct specular reflectioned face region in color image. In: Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance, July, pp. 7-12.
9. Chen C., Luo J., and Parker K. Image segmentation via adaptive K-means clustering and knowledge-based morphological operations with biomedical applications. IEEE Transactions on Image Processing (1998) 1673-1683
10. Comaniciu, D., Meer, P., 1997. Robust analysis of feature spaces: color image segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, San Juan, Puerto Rico, June, pp. 750-755.
11. Conners R.W., and Harlow C.A. A theoretical comparison of texture algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence 2 3 (1980) 204-222
12. Dario, P., Lencioni, M.C., 1997. A microrobotic system for colonoscopy. In: Proceedings of the IEEE International Conference on Robotic and Automation, Florence, Italy, pp. 1567-1572.
13. Deng Y., and Manjunath B.S. Unsupervised segmentation of color-texture regions in images and video. IEEE Transactions on Pattern Analysis and Machine Intelligence (2001)
14. Felipe, J., Traina, A., Traina, C.J., 2003. Retrieval by content of medical images using texture for tissue identification. In: Proceedings of the IEEE Symposium on Computer-Based Medical Systems, June, pp. 175-180.
15. Gevers, T., Stokman, H.M.G., 2000. Classifying Color Transitions into Shadow-Geometry, Illumination Specular reflection or Material Edges. In: Proceedings of the IEEE International Conference on Image Processing, Vancouver, Canada, September, pp. 521-525.
16. Giannakis G., and Heath R.J. Blind identification of multichannel FIR blurs and perfect image restoration. IEEE Transactions on Image Processing 9 11 (2000) 1877-1896
17. Gonzalez R.C. Digital Image Processing (2002), Prentice Hall
18. Hall-Beyer, M., 2000. GLCM Texture: A Tutorial. National Council on Geographic Information and Analysis Remote Sensing Core Curriculum.
19. Han J., and Kamber M. Data Mining: Concepts and Techniques (2001), Morgan Kaufmann Publishers
20. Haralick R., Shanmugam K., and Dinstein I. Textural features for image classification. IEEE Transactions on Systems, Man and Cybernetics (1973) 610-621
21. Khessal, N., Hwa, T., 2000. The development of an automatic robotic colonoscope. In: Proceedings of the TENCON 2000, September, pp. 71-76.
22. Klinker G., Shafer S., and Kanade T. A physical approach to color image understanding. International Journal of Computer Vision 4 1 (1990) 7-38
23. Kundur D., and Hatzinakos D. Blind image deconvolution. IEEE Signal Processing Magazine 13 3 (1996) 43-64
24. Ma, W., Manjunath, B., 1997. Edge flow: a framework of boundary detection and image segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 744-749.
25. McCallum B. Blind deconvolution by simulated annealing. Optics Communication 75 2 (1990) 101-105
26. Meyerhardt J.A., and Mayer R.J. Therapy for colorectal cancer. New England Journal of Medicine 352 5 (2005) 476-487
27. Nakagaki R., and Katsaggelos A. A VQ-based blind image restoration algorithm. IEEE Transactions on Image Processing 12 9 (2003) 1044-1053
28. Pai H., and Bovik A. On eigenstructure-based direct multichannel blind image restoration. IEEE Transactions on Image Processing October (2001) 1434-1446
29. Phee S., and Ng W. Automatic of colonoscopy: visual control aspects. Medicine and Biology Magazine (1998)
30. Ramirez R.W. The FFT, Fundamentals and Concepts (1985), Prentice-Hall
31. Shafarenko L., Petrou M., and Kittler J. Automatic watershed segmentation of randomly textured color images. IEEE Transactions on Image Processing 6 11 (1997) 1530-1544
32. Shafer, S., 1985. Using color to separate reflection components. In: Color Research and Application, pp. 210-218.
33. Shi J., and Malik J. Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 22 8 (2000) 888-905
34. Shuttleworth, J., Todman, A., Naguib, R., Newman, B., Bennett, M., 2002. Colour texture analysis using co-occurrence matrices for classification of colon cancer images. In: Proceedings of the Electrical and Computer Engineering 2002, May, pp. 1134-1139.
35. Sid-Ahmed, M.A., 1995. Image processing: Theory, Algorithms, and Architectures, New York, NY.
36. Society, A.C., 2005. Colorectal Cancer Facts and Figures. American Cancer Society Special Edition 2005, pp. 1-20.
37. Sonka M. Image Processing, Analysis, and Machine Vision (1999), PWS Pub
38. Sucar, L.E., Gillies, D.F., 1990. Knowledge-based assistant for colonoscopy. In: Proceedings of the Third International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, June.
39. Taxt, T., 1994. Separation of the diffuse, specular and quasiperiodic signal components in medical ultrasound images. In: Proceedings of the IEEE Ultrasonics Symposium, November, pp. 1639-1644.
40. Tukey, J.W., 1977. Exploratory Data Analysis. Reading, Massachusetts.
41. van Zyl, J., Cloete, I., 2003. The influence of the number of clusters on randomly expanded data sets. In: Proceedings of the International Conference on Machine Learning and Cybernetics 2003, November, pp. 355-359.
42. Vogt, F., Paulus, D., N.H., 2002. Highlight Substitution in Light Fields. In: Proceedings of the IEEE International Conference on Image Processing, Rochester, USA, September, pp. 637-640.
43. Walker J.S. Fast Fourier transforms (1996), CRC Press
44. Weszka J.S., Dyer C., and Rosenfeld A. A comparative study of texture measures for terrain classification. IEEE Transactions on Systems, Man, and Cybernetics 6 4 (1976) 269-285
45. Witten I.H., and Frank L. Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations (2000), Morgan Kaufmann Publishers
46. Xu, H., Liao, M., 1998. Cluster-based texture matching for image retrieval. In: Proceedings of the International Conference on Image Processing, pp. 766-769.