CTA Coronary Labeling through Efficient Geodesics between Trees Using Anatomy Priors

  • Mehmet A. Gülsün
  • Gareth Funka-Lea
  • Yefeng Zheng
  • Matthias Eckert
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8674)


We present an efficient realization of recent work on unique geodesic paths between tree shapes for the application of matching coronary arteries to a standard model of coronary anatomy in order to label the coronary arteries. Automatically labeled coronary arteries would speed reporting for physicians. The efficiency of the approach and the quality of the results are enhanced using the relative position of detected cardiac structures. We explain how to efficiently compute the geodesic paths between tree shapes using Dijkstra’s algorithm and we present a methodology to account for missing side branches during matching. For nearly all labels our approach shows promise compared with recent work and we show results for 8 additional labels.


coronary labeling shape space tree matching 


  1. 1.
    Austen, W.G., Edwards, J.E., Frye, R.L., et al.: A reporting system on patients evaluated for coronary artery disease. Report of the ad hoc committee for grading of coronary artery disease, council on cardiovascular surgery, American Heart Association. Circulation 51, 5–40 (1975)CrossRefGoogle Scholar
  2. 2.
    Ezquerra, N., Capell, S., Klein, L., Duijves, P.: Model-guided labeling of coronary structure. IEEE Trans. on Medical Imaging 17(3), 429–441 (1998)CrossRefGoogle Scholar
  3. 3.
    Feragen, A., Hauberg, S., Nielsen, M., Lauze, F.: Means in spaces of tree-like shapes. In: ICCV, pp. 736–746 (2011)Google Scholar
  4. 4.
    Feragen, A., Lauze, F., Lo, P., de Bruijne, M., Nielsen, M.: Geometries on spaces of treelike shapes. In: Kimmel, R., Klette, R., Sugimoto, A. (eds.) ACCV 2010, Part II. LNCS, vol. 6493, pp. 160–173. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  5. 5.
    Feragen, A., Lo, P., Gorbunova, V., et al.: An airway tree-shape model for geodesic airway branch labeling. In: Third MICCAI Workshop on Mathematical Foundations of Computational Anatomy (2011)Google Scholar
  6. 6.
    Fiss, D.M.: Normal coronary anatomy and anatomic variations. Applied Radiology 36(1), 14 (2007)Google Scholar
  7. 7.
    Haris, K., Efstratiadis, S.N., Maglaveras, N., Pappas, C., Gourassas, J., Louridas, G.: Model-based morphological segmentation and labeling of coronary angiograms. IEEE Trans. on Medical Imaging 18(10), 1003–1015 (1999)CrossRefzbMATHGoogle Scholar
  8. 8.
    Raff, G.L., Abidov, A., Achenbach, S., et al.: SCCT guidelines for the interpretation and reporting of coronary computed tomographic angiography. J. of Cardiovascular Computed Tomography 3(2), 122–136 (2009)CrossRefGoogle Scholar
  9. 9.
    Yang, G., Broersen, A., Petr, R., et al.: Automatic coronary artery tree labeling in coronary computed tomographic angiography datasets. Computing in Cardiology 38, 109–112 (2011)Google Scholar
  10. 10.
    Zheng, Y., Barbu, A., Georgescu, B., et al.: Four-chamber heart modeling and automatic segmentation for 3-D cardiac CT volumes using marginal space learning and steerable features. IEEE Trans. on Medical Imaging 27(11), 1668–1681 (2008)CrossRefGoogle Scholar
  11. 11.
    Zheng, Y., Tek, H., Funka-Lea, G.: Robust and accurate coronary artery centerline extraction in CTA by combining model-driven and data-driven approaches. In: Mori, K., Sakuma, I., Sato, Y., Barillot, C., Navab, N. (eds.) MICCAI 2013, Part III. LNCS, vol. 8151, pp. 74–81. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  12. 12.
    Zheng, Y., Tek, H., Funka-Lea, G., Zhou, S.K., Vega-Higuera, F., Comaniciu, D.: Efficient detection of native and bypass coronary ostia in cardiac CT volumes: Anatomical vs. pathological structures. In: Fichtinger, G., Martel, A., Peters, T. (eds.) MICCAI 2011, Part III. LNCS, vol. 6893, pp. 403–410. Springer, Heidelberg (2011)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Mehmet A. Gülsün
    • 1
  • Gareth Funka-Lea
    • 1
  • Yefeng Zheng
    • 1
  • Matthias Eckert
    • 2
  1. 1.Imaging and Computer VisionSiemens Corp. TechnologyPrincetonUSA
  2. 2.Friedrich-Alexander-UniversityErlangen-NurembergGermany

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