Automatic left ventricle detection in MRI images using marginal space learning and component-based voting

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 7259, Issue , 2009, Pages

  Zheng, Yefeng ^a   Lu, Xiaoguang ^a   Georgescu, Bogdan ^a   Littmann, Arne ^b   Mueller, Edgar ^b   Comaniciu, Dorin ^a  

^a SIEMENS CORPORATE RESEARCH   (United States)

^b Magnetic Resonance   (Germany)

Author keywords

2D object detection; Component based voting; Heart detection; Marginal space learning

Indexed keywords

2D OBJECTS; AUTOMATIC DETECTION; COMPARATIVE EXPERIMENTS; COMPONENT BASED; DISCRIMINATIVE CLASSIFIERS; FUNCTIONAL MEASUREMENTS; GOLD STANDARDS; HEART DETECTION; IMAGE INTENSITIES; LEFT VENTRICLES; MARGINAL SPACE LEARNING; MRI IMAGE; OBJECT DETECTORS; OBJECT POSE; POSITION DETECTOR; POSITION-ORIENTATION; SYSTEM ROBUSTNESS; TWO-DIMENSION;

CLASSIFIERS; EDUCATION; IMAGE PROCESSING; IMAGING SYSTEMS; LEARNING SYSTEMS; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGING; RESONANCE;

DETECTORS;

EID: 71649096950     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.811045     Document Type: Conference Paper

References (22)

1. Y. Zheng, A. Barbu, B. Georgescu, M. Scheuering, and D. Comaniciu, "Fast automatic heart chamber segmentation from 3D CT data using marginal space learning and steerable features," in Proc. Int'l Conf. Computer Vision, 2007.
2. Y. Zheng, A. Barbu, B. Georgescu, M. Scheuering, and D. Comaniciu, "Four-chamber heart modeling and automatic segmentation for 3D cardiac CT volumes using marginal space learning and steerable features," IEEE Trans. Medical Imaging 27(11), pp. 1668-1681, 2008.
3. W. Rosamond, K. Flegal, K. Furie, A. Go, K. Greenlund, N. Haase, S. M. Hailpern, M. Ho, V. Howard, B. Kissela, S. Kittner, D. Lloyd-Jones, M. McDermott, J. Meigs, C. Moy, G. Nichol, C. O'Donnell, V. Roger, P. Sorlie, J. Steinberger, T. Thom, M. Wilson, and Y. Hong, "Heart disease and stroke statistics-2008 update: A report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee," Circulation 117(4), pp. 25-146, 2008.
4. L. Sugeng, V. Mor-Avi, L.Weinert, J. Niel, C. Ebner, R. Steringer-Mascherbauer, F. Schmidt, C. Galuschky, G. Schummers, R. M. Lang, and H.-J. Nesser, "Quantitative assessment of left ventricular size and function: Side-by-side comparison of real-time three-dimensional echocardiography and computed tomography with magnetic resonance reference," Circulation 114(7), pp. 654-661, 2006.
5. J. Weng, A. Singh, and M. Y. Chiu, "Learning-based ventricle detection from cardiac MR and CT images," IEEE Trans. Medical Imaging 16(4), pp. 378-391, 1997.
6. N. Duta, A. K. Jain, and M.-P. Dubuisson-Jolly, "Learning-based object detection in cardiac MR images," in Proc. Int'l Conf. Computer Vision, pp. 1210-1216, 1999.
7. P. Viola and M. Jones, "Rapid object detection using a boosted cascade of simple features," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 511-518, 2001.
8. B. Georgescu, X. S. Zhou, D. Comaniciu, and A. Gupta, "Database-guided segmentation of anatomical structures with complex appearance," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 429-436, 2005.
9. L. Lu, A. Barbu, M. Wolf, J. Liang, L. Bogoni, M. Salganicoff, and D. Comaniciu, "Simultaneous detection and registration for ileo-cecal valve detection in 3D CT colonography," in Proc. European Conf. Computer Vision, 2008.
10. L. Lu, A. Barbu, M. Wolf, J. Liang, M. Salganicoff, and D. Comaniciu, "Accurate polyp segmentation for 3D CT colongraphy using multi-staged probabilistic binary learning and compositional model," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2008.
11. H. Ling, S. K. Zhou, Y. Zheng, B. Georgescu, M. Suehling, and D. Comaniciu, "Hierarchical, learning-based automatic liver segmentation," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2008.
12. G. Carneiro, F. Amat, B. Georgescu, S. Good, and D. Comaniciu, "Semantic-based indexing of fetal anatomies from 3-D ultrasound data using global/semi-local context and sequential sampling," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2008.
13. X. Lu, B. Georgescu, Y. Zheng, J. Otsuki, R. Bennett, and D. Comaniciu, "Automatic detection of standard planes from three dimensional echocardiographic data," in Proc. IEEE Int'l Sym. Biomedical Imaging, 2008.
14. L. Yang, B. Georgescu, Y. Zheng, P. Meer, and D. Comaniciu, "3D ultrasound tracking of the left ventricles using one-step forward prediction and data fusion of collaborative trackers," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2008.
15. G. Carneiro, B. Georgescu, S. Good, and D. Comaniciu, "Automatic fetal measurements in ultrasound using constrained probabilistic boosting tree," in Proc. Int'l Conf. Medical Image Computing and Computer Assisted Intervention, pp. 571-579, 2007.
16. V. D. Shet, J. Neumann, V. Remesh, and L. S. Davis, "Bilattice-based logical reasoning for human detection," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2007.
17. B. Wu, R. Nevatia, and Y. Li, "Segmentation of multiple, partially occluded objects by grouping, merging, assigning part detection reponses," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2008.
18. P. Felzenszwalb, D. McAllester, and D. Ramanan, "A discriminatively trained, multiscale, deformable part model," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2008.
19. M. Oren, C. Papageorgiou, P. Sinha, E. Osuna, and T. Poggio, "Pedestrian detection using wavelet templates," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 193-199, 1997.
20. Z. Tu, "Probabilistic boosting-tree: Learning discriminative methods for classification, recognition, and clustering," in Proc. Int'l Conf. Computer Vision, pp. 1589-1596, 2005.
21. L. I. Kuncheva, Combining Pattern Classifiers, John Wiley & Sons, 2004.
22. Z. Tu, X. S. Zhou, A. Barbu, L. Bogoni, and D. Comaniciu, "Probabilistic 3D polyp detection in CT images: The role of sample alignment," in Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1544-1551, 2006.