Endoscopic video manifolds

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6362 LNCS, Issue PART 2, 2010, Pages 437-445

  Atasoy, Selen ^a,b   Mateus, Diana ^a   Lallemand, Joe ^a   Meining, Alexander ^c   Yang, Guang Zhong ^b   Navab, Nassir ^a  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^b IMPERIAL COLLEGE LONDON   (United Kingdom)

^c TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

clustering; Endoscopy; manifold learning; video segmentation

Indexed keywords

CLUSTERING; FRAME DETECTION; GI TRACT; HIGH PRECISION; INTER-FRAME; LOW-DIMENSIONAL REPRESENTATION; MANIFOLD LEARNING; OUT-OF-FOCUS BLUR; SIMILARITY MEASURE; SPECULAR HIGHLIGHT; VIDEO SEGMENTATION; VISUAL ASSESSMENTS; VISUALISATION;

IMAGE SEGMENTATION; MEDICAL COMPUTING; MEDICAL IMAGING; VISUALIZATION;

ENDOSCOPY;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; CLUSTER ANALYSIS; COMPUTER ASSISTED DIAGNOSIS; GASTROINTESTINAL ENDOSCOPY; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; CLUSTER ANALYSIS; ENDOSCOPY, GASTROINTESTINAL; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84883842510     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15745-5_54     Document Type: Conference Paper

References (11)

1. Iakovidis, D., Maroulis, D., Karkanis, S.: An intelligent system for automatic detection of gastrointestinal adenomas in video endoscopy. Computers in Biology and Medicine 36, 1084-1103 (2006) (Pubitemid 44163516)
2. Hiremath, P., Dhandra, B., Hegadi, R., Rajput, G.: Abnormality detection in endoscopic images using color segmentation and curvature computation. Neural Information Processing, 834-841 (2004)
3. Li, P., Chan, K., Krishnan, S.: Learning a multi-size patch-based hybrid kernel machine ensemble for abnormal region detection in colonoscopic images. In: CVPR, vol. 2, p. 670 (2005)
4. Oh, J., Hwang, S., Lee, J., Tavanapong, W., Wong, J., de Groen, P.: Informative frame classification for endoscopy video. Medical Image Analysis 11 (2007)
5. Bashar, M., Kitasaka, T., Suenaga, Y., Mekada, Y., Mori, K.: Automatic Detection of Informative Frames from Wireless Capsule Endoscopy Images. Medical Image Analysis (2010)
6. Iakovidis, D., Tsevas, S., Polydorou, A.: Reduction of capsule endoscopy reading times by unsupervised image mining. Comp. Medical Imaging and Graphics (2009)
7. Balasubramanian, M., Schwartz, E., Tenenbaum, J., de Silva, V., Langford, J.: The isomap algorithm and topological stability. Science 295, 7 (2002)
8. Pless, R.: Image spaces and video trajectories: Using isomap to explore video sequences. In: ICCV, pp. 1433 (2003)
9. Belkin, M., Niyogi, P.: Laplacian eigenmaps for dimensionality reduction and data representation. Neural computation 15(6), 1373-1396 (2003) (Pubitemid 37049796)
10. Hartigan, J., Wong, M.: A k-means clustering algorithm. Appl. Stat. 28 (1979)
11. Black, M.J., Anandan, P.: A framework for the robust estimation of optical flow. In: ICCV, vol. 93, pp. 231-236 (1993)