Medical Image Analysis
Volume 14, Issue 2 , Pages 160-171 , April 2010

Multiple hypothesis template tracking of small 3D vessel structures

Received 1 November 2008 ,Revised 7 October 2009 ,Accepted 8 December 2009.

References 

  1. Adams R, Bischof L. Seeded region growing. IEEE Transactions on Pattern Analysis and Machine Intelligence. 1994;16(6):641–647
  2. Aylward SR, Bullitt E. Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction. IEEE Transactions on Medical Imaging. 2002;21(2):61–75
  3. Behrens T, Rohr K, Stiehl HS. 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. 2003;33(4):554–561
  4. Bhalerao, A., Thönnes, E., Kendall, W., Wilson, R., 2001. Inferring vascular structure from 2D and 3D imagery. In: Medical Image Computing and Computer-assisted Intervention (MICCAI’01), 2001, pp. 820–828.
  5. Björck Å. Numercial Methods for Least Squares Problems. SIAM; 1996;
  6. Blackman SS. Multiple hypothesis tracking for multiple target tracking. IEEE Aerospace and Electronic Systems Magazine. 2004;19(1):5–18
  7. Bühler K, Felkel P, Cruz AL. Geometric methods for vessel visualization and quantification – a survey. In:  Brunnett HMG,  Hamann B editor. Geometric Modelling for Scientific Visualization. Springer; 2003;p. 399–421
  8. Canero C, Radeva P. Vesselness enhancement diffusion. Pattern Recognition Letters. 2003;24(16):3141–3151
  9. Chaudhuri S, Chatterjee S, Katz N, Nelson M, Goldbaum M. Detection of blood vessels in retinal images using two dimensional matched filters. IEEE Transactions on Medical Imaging. 1989;8(3):263–269
  10. Chen J, Amini AA. Quantifying 3-D vascular structures in MRA images using hybrid PDE and geometric deformable models. IEEE Transactions on Medical Imaging. 2004;23(10):1251–1262
  11. Chung FRK. Spectral Graph Theory. American Mathematical Society; 1997;
  12. Deschamps T, Cohen LD. Fast extraction of minimal paths in 3D images and application to virtual endoscopy. Medical Image Analysis. 2001;5(4):281–299
  13. Deschamps, T., Cohen, L.D., 2002. Fast extraction of tubular and tree 3D surfaces with front propagation methods. In: 16th International Conference on Pattern Recognition (ICPR’02), 2002, pp. 731–734.
  14. Draper NR, Smith H. Applied Regression Analysis. 3rd ed.. New York: Wiley; 1998;
  15. Florin C, Paragios N, Williams J, filters Particle. A quasi-Monte Carlo solution for segmentation of coronaries. In: Medical Image Computing and Computer-assisted Intervention (MICCAI’05). LNCS. vol. 3749:Berlin/Heidelberg: Springer; 2005;p. 246–253
  16. Frangi, A.F., Niessen, W.J., Vincken, K.L., Viergever, M.A., 1998. Multiscale vessel enhancement filtering. In: Medical Image Computing and Computer-assisted Intervention (MICCAI’98), 1998, pp. 130–137.
  17. Friman, O., Hindennach, M., Peitgen, H.-O., 2008. Template-based multiple hypotheses tracking of small vessels. In: Proc. IEEE Int. Symp. Biom. Imaging (ISBI’08), 2008, pp. 1047–1050.
  18. Friman, O., Kühnel, C., Peitgen, H.-O., 2008. Artery centerline extraction using multiple hypothesis tracking and minimal paths. In: 3D Segmentation in the Clinic: A Grand Challenge II Workshop, Medical Image Computing and Computer Assisted Intervention (MICCAI’08), 2008.
  19. Gill PE, Murray W. Algorithms for the solution of the nonlinear least-squares problem. SIAM Journal on Numerical Analysis. 1978;15(5):977–992
  20. Gooya A, Liao H, Matsumiya K, Masamune K, Dohi T. Effective statistical edge integration using a flux maximizing scheme for volumetric vascular segmentation in MRA. In: Information Processing in Medical Imaging (IPMI’07). Berlin/Heidelberg: Springer; 2007;p. 86–97
  21. Kirbas C, Quek F. A review of vessel extraction techniques and algorithms. ACM Computing Surveys. 2004;36(2):81–121
  22. Krissian K. Flux-based anisotropic diffusion: application to enhancement of 3D angiogram. IEEE Transactions on Medical Imaging. 2002;22(11):1440–1442
  23. Krissian K, Malandain G, Ayache N, Vaillant R, Trousset Y. Model based detection of tubular structures in 3D images. Computer Vision and Image Understanding. 2000;80(2):130–171
  24. Krissian, K., Wu, X., Luboz, V., 2006. Smooth vasculature reconstruction with circular and elliptic cross sections. In: Medicine Meets Virtual Reality Conference (MMVR’06), 2006.
  25. La Cruz, A., Straka, M., Köchl, A., Srámek, M., Gröller, E., Fleischmann, D., 2004. Non-linear model fitting to parameterize diseased blood vessels. In: Proceedings of IEEE Visualization, 2004, pp. 393–400.
  26. Lee J, Beighley P, Ritman E, Smith N. Automatic segmentation of 3D micro-CT coronary vascular images. Medical Image Analysis. 2007;11(6):630–647
  27. Lesage D, Angelini ED, Bloch I, Funka-Lea G. A review of 3D vessel lumen segmentation techniques: models, features and extraction schemes. Medical Image Analysis. 2009;13(6):819–845
  28. Lorigo LM, Faugeras OD, Grimson WEL, Keriven R, Kikinis R, Nabavi A, et al. CURVES: curve evolution for vessel segmentation. Medical Image Analysis. 2001;5(3):195–206
  29. Manniesing, R., Niessen, W.J., 2004. Local speed functions in level set based vessel segmentation. In: Medical Image Computing and Computer-assisted Intervention (MICCAI’04), vol. 3217 of LNCS, 2004, pp. 475–482.
  30. Manniesing R, Viergever MA, Niessen WJ. Vessel enhancing diffusion – a scale space representation of vessel structures. Medical Image Analysis. 2006;10(6):815–825
  31. Manniesing R, Velthuis BK, van Leeuwen MS, van der Schaaf IC, van Laar PJ, Niessen WJ. Level set based cerebral vasculature segmentation and diameter quantification in CT angiography. Medical Image Analysis. 2006;10(2):200–214
  32. Manniesing R, Viergever MA, Niessen WJ. Vessel axis tracking using topology constrained surface evolution. IEEE Transactions on Medical Imaging. 2007;26(3):309–316
  33. McIntosh, C., Hamarneh, G., 2006. Vessel crawlers: 3D physically-based deformable organisms for vasculature segmentation and analysis. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’06), 2006, pp. 1084–1091.
  34. Metz, C., Schaap, M., van Walsum, T., van der Giessen, A., Weustink, A., Mollet, N., Krestin, G., Niessen, W., 2008. 3D segmentation in the clinic: a grand challenge II – coronary artery tracking. In: 3D Segmentation in the Clinic: A Grand Challenge II Workshop, Medical Image Computing and Computer Assisted Intervention (MICCAI’08), 2008.
  35. Miles FP, Nuttall AL. Matched filter estimation of serial blood vessel diameters from video images. IEEE Transactions Medical Imaging. 1993;12(2):147–152
  36. Nain D, Yezzi A, Turk G. Vessel segmentation using a shape driven flow. In: Medical Image Computing and Computer-assisted Intervention (MICCAI’04). LNCS. vol. 3216:Berlin/Heidelberg: Springer; 2004;p. 51–59
  37. Noordmans HJ, Smeulders AWM. High accuracy tracking of 2D/3D curved line-structures by consecutive cross-section matching. Pattern Recognition Letters. 1998;19(1):97–111
  38. O’Brien, J.F., Ezquerra, N.F., 1994. Automated segmentation of coronary vessels in angiographic image sequences utilizing temporal, spatial structural constraints. In: SPIE Visualization in Biomedical Computing, 1994, pp. 25–37.
  39. Olabarriaga SD, Breeuwer M, Niessen WJ. Minimum cost path algorithm for coronary artery central axis tracking in CT images. In: Medical Image Computing and Computer-assisted Intervention (MICCAI’03). vol. 2879:Berlin/Heidelberg: Springer; 2003;p. 687–694
  40. Reid DB. An algorithm for tracking multiple targets. IEEE Transactions on Automatic Control. 1979;24(6):843–854
  41. Rossignac, J., Whited, B., Slabaugh, G., Fang, T., Unal, G., 2007. Pearling: 3D interactive extraction of tubular structures from volumetric images. In: Medical Image Computing and Computer-assisted Intervention (MICCAI’07), 2007.
  42. Sato, Y., Nakajima, S., Atsumi, H., Koller, T., Gerig, G., Yoshida, S., Kikinis, R., 1997. 3D multi-scale line filter for segmentation and visualization of curvilinear structures in medical images. In: 1st Joint Conference Computer Vision, Virtual Reality and Robotics in Medicine and Medical Robotics and Computer-Assisted Surgery, vol. 1205, 1997.
  43. Schaap M, Smal I, Metz C, van Walsum T, Niessen W. Bayesian tracking of elongated structures in 3D images. In: Information Processing in Medical Imaging (IPMI’07). LNCS. vol. 4584:Berlin/Heidelberg: Springer; 2007;p. 74–85
  44. Schaap M, Metz C, van Walsum T, van der Giessen A, Weustink A, Mollet N, et al. Standardized evaluation methodology and reference database for evaluating coronary artery centerline extraction algorithms. Medical Image Analysis. 2009;13(5):701–714
  45. Shim H, Kwon D, Yun ID, Lee SU. Robust segmentation of cerebral arterial segments by a sequential Monte Carlo method: particle filtering. Comput Methods and Programs in Biomedicine. 2006;84(2–3):135–145
  46. Suri JS, Liu K, Reden L, Laxminarayan S. A review on MR vascular image processing: skeleton versus non-skeleton approaches: part II. IEEE Transactions on Information Technology in Biomedicine. 2002;6(4):338–350
  47. Tyrrell JA, di Tomaso E, Fuja D, Tong R, Kozak K, Jain RK, et al. Robust 3-D modeling of vasculature imagery using superellipsoids. IEEE Transactions on Medical Imaging. 2007;26(2):223–237
  48. Vasilevskiy A, Siddiqi K. Flux maximizing geometric flows. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2002;24(12):1565–1578
  49. Wan S-Y, Higgins WE. Symmetric region growing. IEEE Transactions on Image Processing. 2003;12(9):1007–1015
  50. Wink O, Niessen WJ, Viergever MA. Fast delineation and visualization of vessels in 3D angiographic images. IEEE Transactions on Medical Imaging. 2000;19(4):337–346
  51. Wong W, Chung A. Probabilistic vessel axis tracing and its application to vessel segmentation with stream surfaces and minimum cost paths. Medical Image Analysis. 2007;11(6):567–587
  52. Wörz S, Rohr K. Segmentation and quantification of human vessels using a 3-D cylindrical intensity model. IEEE Transactions on Image Processing. 2007;16(8):1994–2004
  53. Wörz, S., Rohr, K., 2007. 3D adaptive model-based segmentation of human vessels. In: Proc. SPIE Medical Imaging 2007: Physiology, Function, and Structure from Medical Images (MI’07), 2007.
  54. Yan P, Kassim AA. Segmentation of volumetric MRA images by using capillary active contour. Medical Image Analysis. 2006;10(3):317–329
  55. Yang, Y., Stillman, A., Tannenbaum, A., Giddens, D., 2007. Automatic segmentation of coronary arteries using Bayesian driven implicit surfaces. In: 4th IEEE International Symposium on Biomedical Imaging (ISBI’07), 2007, pp. 189–192.
  56. Zambal, S., Hladuvka, J., Kanitsar, A., Bühler, K., 2008. Shape and appearance models for automatic coronary artery tracking. In: 3D Segmentation in the Clinic: A Grand Challenge II Workshop, Medical Image Computing and Computer Assisted Intervention (MICCAI’08), 2008.

PII: S1361-8415(09)00147-9

doi: 10.1016/j.media.2009.12.003

Medical Image Analysis
Volume 14, Issue 2 , Pages 160-171 , April 2010