Abstract
We present an efficient method for the segmentation and axis extraction of vessels and other curvilinear structures in volumetric medical images. The image is treated as a graph from which the user selects seed points to be connected via 1-dimensional paths. A variant of Dijkstra’s algorithm both grows the segmenting surface from initial seeds and connects them with a minimal path computation. The technique is local and does not require examination or pre-processing of the entire volume. The surface propagation is controlled by iterative computation of border probabilities. As expanding regions meet, the statistics collected during propagation are passed to an active minimal-path generation module which links the associating points through the vessel tree. We provide a probabilistic basis for the volume search and path-finding speed functions and then apply the algorithm to phantom and real data sets. This work focuses on the contrast-enhanced magnetic resonance angiography (CE-MRA) and computed tomography angiography (CTA) domains, although the framework is adaptable for other purposes.
Chapter PDF
Similar content being viewed by others
References
Andrews, F.C.: Equilibrium Statistical Mechanics, 2nd edn. John Wiley & Sons, Inc., New York (1975)
Malladi, R., Sethian, J.A.: A Real-Time Algorithm for Medical Shape Recovery. In: Proceedings of International Conference on Computer Vision, Mumbai, India, pp. 304–310 (January 1998)
Masutani, Y., Schiemann, T., Hohne, K.: Vascular Shape Segmentation and Structure Extraction Using a Shape-Based Region-Growing Model. In: Wells, W.M., Colchester, A.C.F., Delp, S.L. (eds.) MICCAI 1998. LNCS, vol. 1496, pp. 1242–1249. Springer, Heidelberg (1998)
Mclnerney, T., et al.: Medical Image Segmentation Using Topologically Adaptable Surfaces. In: Troccaz, J., Mösges, R., Grimson, W.E.L. (eds.) CVRMed-MRCAS 1997, CVRMed 1997, and MRCAS 1997. LNCS, vol. 1205, pp. 23–32. Springer, Heidelberg (1997)
Sethian, J.: A Fast Marching Level Set Method for Monotonically Advancing Fronts. Proceedings of the National Academy of Sciences 93, 1591–1595 (1996)
Sethian, J.: Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science, 2nd edn. Cambridge University Press, Cambridge (1999)
Tek, H., Kimia, B.: Volumetric Segmentation of Medical Images by Three-Dimensional Bubbles. CVIU 64(2), 246–258 (1997)
Zhu, S., Yuille, A.: Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 18(9) (September 1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Avants, B.B., Williams, J.P. (2000). An Adaptive Minimal Path Generation Technique for Vessel Tracking in CTA/CE-MRA Volume Images. In: Delp, S.L., DiGoia, A.M., Jaramaz, B. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2000. MICCAI 2000. Lecture Notes in Computer Science, vol 1935. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-40899-4_73
Download citation
DOI: https://doi.org/10.1007/978-3-540-40899-4_73
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-41189-5
Online ISBN: 978-3-540-40899-4
eBook Packages: Springer Book Archive