Abstract
In this paper a method to extract cerebral arteries from computed tomographic angiography (CTA) is proposed. Since CTA shows both bone and vessels, the examination of vessels is a difficult task. In the upper part of the brain, the arteries of main interest are not close to bone and can be well segmented out by thresholding and simple connected-component analysis. However in the lower part the separation is challenging due to the spatial closeness of bone and vessels and their overlapping intensity distributions. In this paper a CTA volume is partitioned into two sub-volumes according to the spatial relationship between bone and vessels. In the lower sub-volume, the concerning arteries are extracted by tracking the center line and detecting the border on each cross-section. The proposed tracking method can be characterized by the adaptive properties to the case of cerebral arteries in CTA. These properties improve the tracking continuity with less user-interaction.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Rinkel, G.J.E., Djibuti, M., Algra, A., Gijn, J.V.: Prevalence and risk of rupture of intracranial aneurysms: a systematic review. Stroke 29, 251–256 (1998)
Higgins, W.E., Spyra, W.J.T.: Automatic extraction of the arterial tree from 3-d angiograms. In: IEEE Conf. Eng. in Medicine and Bio., vol. 2, pp. 563–564 (1989)
Sonka, M., Fitzpatrick, J.M.: Handbook of Medical Imaging. SPIE Press, Bellingham (2000)
Flasque, N., Desvignes, M., Constans, J., Revenu, M.: Acquisition, segmentation, and tracking of the cerebral vascular tree on 3D magnetic resonance angiography images. Medical Image Analysis 5, 173–183 (2001)
Sabry Hassouna, M., Sites, C.B., Farag, A.A., Hushek, S.: A Fast Automatic Method for 3D Volume Segmentation of the Human Cerebrovascular. In: CARS (2002)
Wilson, D.L., Noble, J.A.: An Adaptive Segmentation Algorithm for Time-of-flight MRA Dat. IEEE Trans. on Medical Imaging 18, 938–945 (1999)
Chapman, B.E., Stapelton, J.O., Parker, D.L.: Intracranial vessel segmentation from time-of-flight MRA using pre-processing of the MIP Z-buffer: accuracy of the ZBS algorithm. Medical Image Analysis 8, 113–126 (2004)
Suryanarayanan, S., Mullick, R., Mallya, Y., Kamath, V.: Automatic Partitioning of Head CTA for enabling Segmentation. In: SPIE Proceedings of Medical Imaging (2004)
Wink, O., Niessen, W.J., Viergever, M.A.: Fast Delineation and Visualization of Vessels in 3-D Angiographic Images. IEEE Trans. on Medical Imaging 19, 337–346 (2000)
Hong, H., Lee, H., Shin, Y.G., Seong, Y.H.: Three-Dimensional Brain CT-DSA using Rigid Registration and Bone Masking for Early Diagnosis and Treatment Planning, vol. 3378 (2004)
Zwillinger, D. (ed.): Spherical Coordinates in Space, 4.9.9 in CRC Standard Mathematical Tables and Formulae, pp. 297–298. CRC Press, Boca Raton (1995)
Open Source Computer Vision Library: Reference Manual, Intel Co (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Shim, H., Yun, I.D., Lee, K.M., Lee, S.U. (2005). Partition-Based Extraction of Cerebral Arteries from CT Angiography with Emphasis on Adaptive Tracking. In: Christensen, G.E., Sonka, M. (eds) Information Processing in Medical Imaging. IPMI 2005. Lecture Notes in Computer Science, vol 3565. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11505730_30
Download citation
DOI: https://doi.org/10.1007/11505730_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26545-0
Online ISBN: 978-3-540-31676-3
eBook Packages: Computer ScienceComputer Science (R0)