Echocardiogram view classification using edge filtered scale-invariant motion features

2009 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009

Volumn , Issue , 2009, Pages 723-730

  Kumar, Ritwik ^a   Wang, Fei ^b   Beymer, David ^b   Syeda Mahmood, Tanveer ^b  

^a University of Florida   (United States)

^b IBM ALMADEN RESEARCH CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; HEART; INFORMATION FILTERING; PROBES; SUPPORT VECTOR MACHINES; ULTRASONIC APPLICATIONS;

CARDIAC STRUCTURE; CLASSIFICATION TESTS; HIERARCHICAL FEATURES; KINETIC INFORMATION; SALIENT FEATURES; STATE-OF-THE-ART METHODS; ULTRASOUND PROBES; VIDEO CLASSIFICATION;

CLASSIFICATION (OF INFORMATION);

EID: 70450174317     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2009.5206838     Document Type: Conference Paper

References (20)

1. S. Aschkenasy, C. Jansen, R. Osterwalder, A. Linka, M. Unser, S. Marsch, and P. Hunziker. Unsupervised image classification of medical ultrasound data by multiresolution elastic registration. Ultrasound in Medicine and Biology, 32(7):1047-1054, 2006.
2. D. R. Bailes. The use of the gray level sat to find the salient cavities in echocardiograms. Journal of Visual Communication and Image Representation, 7(2):169-195, 1996.
3. D. Beymer, T. Syeda-Mahmood, and F. Wang. Exploiting spatio-temporal information for view recognition in cardiac echo videos. In IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA), pages 1-8, 2008.
4. N. Dalal, B. Triggs, and C. Schmid. Human detection using oriented histograms of flow and appearance. In ECCV, 2006.
5. P. Dollar, V. Rabaud, G. Cottrell, and S. Belongie. ehavior recognition via sparse spatio-temporal features. In 2nd joint IEEE international workshop on visual surveillance and performance evaluation of tracking and surveillance, 2005.
6. S. Ebadollahi, S. Chang, and H. Wu. Automatic view recognition in echocardiogram videos using parts-based representation. In CVPR, pages 2-9, 2004.
7. A. A. Efros, A. C. Berg, G. Mori, and J. Malik. Recognizing action at a distance. In ICCV, 2003.
8. K. Grauman and T. Darrell. The pyramid matching kernel: Discriminative classification with sets of image features. In ICCV, 2005.
9. K. Grauman and T. Darrell. Approximate correspondences in high dimensions. In NIPS, 2006.
10. A. Guimond, A. Roche, N. Ayache, and J. Meunier. Threedimensional multimodal brain warping using the demons algorithm and adaptive intensity corrections. IEEE Transactions on Medical Imaging, 20(1):58-69, 2001.
11. H. Jhuang, T. Serre, L. Wolf, and T. Poggio. A biologically inspired system for action recognition. In ICCV, 2007.
12. Y. Ke, R. Sukthankar, and M. Hebert. Efficient visual eventusing volumetric features. In ICCV, 2005.
13. I. Laptev. On space-time interest points. IJCV, 2005.
14. I. Laptev, M. Marszaek, C. Schmid, and B. Rozenfeld. Learning realistic human actions from movies. In CVPR, 2008.
15. D. G. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 60(2):91-110, 2004.
16. M. Otey, J. Bi, S. Krishna, B. Rao, J. Stoeckel, A. S. Katz, J. Han, and S. Parthasarathy. Automatic view recognition for cardiac ultrasound images. In MICCAI: Intl Workshop on Computer Vision for Intravascular and Intracardiac Imaging, pages 187-194, 2006.
17. J. Park, S. Zhou, C. Simopoulos, J. Otsuki, and D. Comaniciu. Automatic cardiac view classification of echocardiogram. In ICCV, pages 1-8, 2007.
18. A. Roy, S. Sural, J. Mukherjee, and A. K. Majumdar. Statebased modeling and object extraction from echocardiogram video. IEEE Transactions on Information Technology in Biomedicine, 12(3):366-376, 2008.
19. H. Sidenbladh and M. J. Black. Learning the statistics of people in images and video. IJCV, 54:54-61, 2003.
20. S. Zhou, J. Park, B. Georgescu, J. Simopoulos, J. Otsuki, and D. Comaniciu. Image-based multiclass boosting and echocardiographic view classification. In CVPR, pages 1559-1565, 2006.