Robust segmentation of tubular structures in 3-D medical images by parametric object detection and tracking

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 33, Issue 4, 2003, Pages 554-561

  Behrens, Thorsten ^a   Rohr, Karl ^b   Stiehl, Siegfried ^c  

^a SUN MICROSYSTEMS   (United States)

^b International University in Germany   (Germany)

^c UNIVERSITY OF HAMBURG   (Germany)

Author keywords

3 D medical images; Generalized cylinders; Kalman filter; Minimal user interaction; Randomized hough transform (RHT); Spatial tracking

Indexed keywords

ALGORITHMS; HOUGH TRANSFORMS; IMAGE SEGMENTATION; KALMAN FILTERING; OBJECT RECOGNITION; THREE DIMENSIONAL COMPUTER GRAPHICS;

GENERALIZED CYLINDERS; MINIMAL USER INTERACTION;

MEDICAL IMAGING;

EID: 0042767034     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2003.814305     Document Type: Article

References (24)

1. T. O. Binford, Visual perception by computer, in IEEE Conf. Systems, Science Cybernetics, Miami, FL, 1971. Invited paper at.
2. J. F. Canny, "A computational approach to edge detection," IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-8, pp. 679-697, 1986.
3. W. Feller, An Introduction to Probability Theory and Its Applications, 3rd ed. New York: Wiley, 1968, vol. 1.
4. M. A. Fischer and R. C. Bolles, "Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography," Commun. ACM, vol. 24, no. 6, pp. 381-395, 1981.
5. A. B. Forbes, "Fitting an Ellipse to Data," National Physical Laboratory, Teddington, U.K., Tech. Rep. DITC 95/87, 1987.
6. A. F. Frangi, W. J. Niessen, R. M. Hoogeveern, Th. van Walsum, and M. A. Viergver, "Quantitation of vessel morphology from 3-D MRA," in Proc. MICCAI, 1999, pp. 358-367, LNCS 1679.
7. M. Hernández-Hoyos, A. Anwander, M. Orkisz, J.-P. Roux, P. Douek, and I. E. Magnin, "A deformable vessel model with single point initialization for segmentation, quantification and visualization of blood vessels in 3-D MRA," in Proc. MICCAI, 2000, pp. 735-745.
8. J. Illingworth and J. Kittler, "A survey of the Hough transform," Comput. Vis., Graph. Image Process., vol. 44, no. 1, pp. 87-116, 1988.
9. R. E. Kalman, "A new approach to linear filtering and prediction problems," Trans. ASME J. Basic Eng., vol. 82, no. 35-45, 1960.
10. H. Kälviäinen, P. Kirvonen, L. Xu, and E. Oja, "Comparisons of probabilistic and nonprobabilistic Hough transforms," in Proc. 3rd ECCV, 1994, pp. 351-360, LNCS 800.
11. T. M. Koller, G. Gerig, G. Székely, and D. Dettwiler, "Multiscale detection of curvilinear structures in 2-D and 3-D image data," in Proc. 5th Int. Conf. Computer Vision. Los Alamitos, CA, 1995, pp. 864-869.
12. K. Krissian, G. Malandain, N. Ayache, R. Vaillant, and Y. Trousset, "Model based multiscale detection of 3-D vessels," Proc. IEEE Workshop Biomedical Image Analysis, pp. 202-210, 1998.
13. V. Kyrki and H. Kälviäinen, "Combination of local and global line extraction," Real-Time Imaging, vol. 6, pp. 79-91, 2000.
14. V. F. Leavers, Shape Detection in Computer Vision Using the Hough Transform. Berlin, Germany: Springer-Verlag, 1992, p. 151.
15. ____, "Survey: Which Hough transform?," Comput. Vis., Graph. Image Process, vol. 58, no. 2, pp. 250-264, 1993.
16. C. Lorenz, I.-C. Carlsen, T. M. Buzug, C. Fassnacht, and J. Weese, "Multi-scale line segmentation with automatic estimation of width, contrast and tangential direction in 2-D and 3-D medical images," in Proc. CVRMed-MRCAS 1997, 1997, pp. 233-242, LNCS 1205.
17. T. McInerney and D. Terzopoulos, "Deformable models in medical image analysis: A survey," Med. Image Anal., vol. 1, no. 2, pp. 91-108, 1996.
18. D. Shaked, O. Yaron, and N. Kiryati, "Deriving stopping rules for the probabilistic Hough transform by sequential analysis," Comput. Vis. Image Understand., vol. 63, no. 3, pp. 512-526, 1996.
19. U. Shani, "A 3-D model-driven system for the recognition of abdominal anatomy from CT scans," in Proc. 5th Int. Conf. Pattern Recognition, vol. 1. Los Alamitos, CA, 1980, pp. 585-591.
20. G. Stetten and S. M. Pizer, "Automated identification and measurement of objects via populations of medial primitives, with application to real time 3-D echocardiography," in Proc. 16th Int. Conf. Information Processing in Medical Imaging, 1999, pp. 84-99, LNCS 1613.
21. A. J. Walker, "An efficient method for generating discrete random variables with general distributions," ACM Trans. Math. Softw., vol. 3, no. 3, pp. 253-256, 1977.
22. O. Wink, W. J. Niessen, and M. A. Viergever, "Fast quantification of abdominal aortic aneurysms from CTA volumes," in Proc. MICCAI, 1998, pp. 138-145, LNCS 1496.
23. L. Xu and E. Oja, "Randomized Hough transform (RHT): Basic mechanisms, algorithms, and computational complexities," Comput. Vis. Graph. Image Process., vol. 57, no. 2, pp. 131-154, 1993.
24. L. Xu, E. Oja, and P. Kultanen, "A new curve detection method: Randomized Hough transform (RHT)," Pattern Recognit. Lett., vol. 11, no. 5, pp. 331-338, 1990.