Share Email Print

Proceedings Paper

A method for semi-automatic segmentation and evaluation of intracranial aneurysms in bone-subtraction computed tomography angiography (BSCTA) images
Author(s): Susanne Krämer; Hendrik Ditt; Christina Biermann; Michael Lell; Jörg Keller
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

The rupture of an intracranial aneurysm has dramatic consequences for the patient. Hence early detection of unruptured aneurysms is of paramount importance. Bone-subtraction computed tomography angiography (BSCTA) has proven to be a powerful tool for detection of aneurysms in particular those located close to the skull base. Most aneurysms though are chance findings in BSCTA scans performed for other reasons. Therefore it is highly desirable to have techniques operating on standard BSCTA scans available which assist radiologists and surgeons in evaluation of intracranial aneurysms. In this paper we present a semi-automatic method for segmentation and assessment of intracranial aneurysms. The only user-interaction required is placement of a marker into the vascular malformation. Termination ensues automatically as soon as the segmentation reaches the vessels which feed the aneurysm. The algorithm is derived from an adaptive region-growing which employs a growth gradient as criterion for termination. Based on this segmentation values of high clinical and prognostic significance, such as volume, minimum and maximum diameter as well as surface of the aneurysm, are calculated automatically. the segmentation itself as well as the calculated diameters are visualised. Further segmentation of the adjoining vessels provides the means for visualisation of the topographical situation of vascular structures associated to the aneurysm. A stereolithographic mesh (STL) can be derived from the surface of the segmented volume. STL together with parameters like the resiliency of vascular wall tissue provide for an accurate wall model of the aneurysm and its associated vascular structures. Consequently the haemodynamic situation in the aneurysm itself and close to it can be assessed by flow modelling. Significant values of haemodynamics such as pressure onto the vascular wall, wall shear stress or pathlines of the blood flow can be computed. Additionally a dynamic flow model can be generated. Thus the presented method supports a better understanding of the clinical situation and assists the evaluation of therapeutic options. Furthermore it contributes to future research addressing intervention planning and prognostic assessment of intracranial aneurysms.

Paper Details

Date Published: 13 March 2009
PDF: 11 pages
Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 726120 (13 March 2009); doi: 10.1117/12.811521
Show Author Affiliations
Susanne Krämer, Fern Univ. in Hagen (Germany)
Hendrik Ditt, Siemens Healthcare (Germany)
Christina Biermann, Siemens Healthcare (Germany)
Eberhard-Karls-Univ. of Tuebingen (Germany)
Michael Lell, Institute of Diagnostic Radiology, Univ. of Erlangen-Nuremberg (Germany)
Jörg Keller, Fern Univ. in Hagen (Germany)

Published in SPIE Proceedings Vol. 7261:
Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling
Michael I. Miga; Kenneth H. Wong, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?