Abstract
Topological abstraction of complex and highly branching three- dimen-sional structures to a tree-like skeleton enables sophisticated object recognition and analysis in 3D image data sets. Skeletonization is a costly procedure, mostly not applicable with huge data sets, e.g. computed tomography studies from lungs or liver. Information about the hierarchical topology of vessel trees would be highly desirable in these cases. A fast morphological thinning approach for skeletonization of tubular structures and objects with arbitrary shape was developed. This algorithm increases hit-rate during surface erosion applying minimal constraints to generality, providing performance suitable for thinning of huge datasets. Time consuming neighbourhood checking is solved by the use of fast indexing lookup tables, yielding homogenous erosion of any shape. Results show accurate centreline extraction without any offset introduced by digital sampling of objects with even diameter. The algorithm proved to be robust and fast, meeting the requirements of computer aided diagnosis in modern radiology.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Anelli, G., Broggi, A., Destri, G.: Toward The Optimal Decomposition Of Arbitrary Shaped Structuring Elements By Means of Genetic Approach. In: Mathematical Morphology and its Application to Image and Signal Processing, pp. 227–234. Kluwer Academic Publisher, Dordrecht (1996)
Chazal, F., Soufflet, R.: Stability and finiteness properties of Medial Axis and Skeleton. Journal of Dynamical and Control Systems 10(2), 149–170 (2004)
Gonzales, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. Prentice-Hall Inc., Upper Saddle River (2001)
Jonker, P.P.: Skeletons in N dimensions using shape primitives. Pattern Recognition Letters 23, 677–686 (2002)
Jonker, P.P.: Discrete topology on N-dimensional square tessellated grids. Image and Vision Computing 23(2), 213–225 (2005)
Lohou, C., Bertrand, G.: A new 3D 12-subiteration thinning algorithm based on P-simple points. In: Proc. IWCIA 2001. Electronic Notes in Theoretical Computer Science, vol. 46 (2001)
Nikopoulos, N., Pitas, I.: A fast implementation of 3D binary morphogical transformations. IEEE Transactions on Image Processing 9(2), 291–294 (2000)
Palagyi, K., Tschirren, J., Hoffmann, E.A., Sonka, M.: Quantitative analysis of pulmonary airway tree structures. Computers in Biology and Medicine 36, 974–996 (2006)
Park, H., Chin, R.T.: Decomposition of Arbitrarily Shaped Morphological Structuring Elements. IEEE Transactions on Pattern Analysis and Machine Intelligence 17, 2–15 (1995)
Serra, J.: Image Analysis and Mathematical Morphology. Academic Press, London (1982)
Soille, P., Breen, E.J., Jones, R.: Recursive Implementation of Erosions and Dilations Along Discrete Lines At Arbitrary Angles. IEEE Trans. on Pattern Analysis and Machine Intelligence (1996)
Vincent, L.: Morphological transformations of binary images with arbitrary structuring elements. Signal Processing 22, 3–23 (1991)
Zwettler, G., Swoboda, R., Backfrieder, W., Steinwender, C., Leisch, F., Gabriel, C.: Robust Segmentation of Coronary Arteries in Cine Angiography for 3D Modeling. In: International Mediterranean Modelling Multiconference IMM 2006, Barcelona, Spain, pp. 675–680 (2006)
Zwettler, G., Swoboda, R., Pfeifer, F., Backfrieder, W.: Accelerated Skeletonization Algorithm for Tubular Structures in Large Datasets by Randomized Erosion. In: Proc. of International Conference on Computer Vision Theory and Applications VISAPP, pp. 74–81 (2008)
Zwettler, G., Swoboda, R., Pfeifer, F., Kratochwill, H., Fellner, F., Backfrieder, W.: Automatische Klassifizierung der Leber aus hochauflösenden Multi-Slice CT Daten. In: Proc. of Fachhochschul Forschungs Forum FFH 2007 (2007)
Zwettler, G., Swoboda, R., Pfeifer, F., Backfrieder, W.: Fast Skeletonization for Medial Axis Extraction on Tubular Large 3D Data. In: Challenges in Biosciences: Image Analysis and Pattern Recognition Aspects, St. Magdalena, Linz, Austria, pp. 91–102 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zwettler, G., Swoboda, R., Pfeifer, F., Backfrieder, W. (2009). Fast Medial Axis Extraction Algorithm on Tubular Large 3D Data by Randomized Erosion. In: Ranchordas, A., Araújo, H.J., Pereira, J.M., Braz, J. (eds) Computer Vision and Computer Graphics. Theory and Applications. VISIGRAPP 2008. Communications in Computer and Information Science, vol 24. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10226-4_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-10226-4_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10225-7
Online ISBN: 978-3-642-10226-4
eBook Packages: Computer ScienceComputer Science (R0)