A Segmentation Method for Stentgrafts in the Abdominal Aorta from ECG-gated CTA Data

Klein, A. and Renema, W.K.J. and Oostveen, L.J. and Schultze Kool, L.J. and Slump, C.H. (2008) A Segmentation Method for Stentgrafts in the Abdominal Aorta from ECG-gated CTA Data. In: Proceedings of SPIE Medical Imaging 2008, 17 - 21 Feb 2008, San Diego, USA.

PDF
Restricted to UT campus only: Request a copy
279Kb

Abstract:	Endovascular aortic replacement (EVAR) is an established technique, which uses stentgrafts to treat aortic aneurysms in patients at risk of aneurysm rupture. The long-term durability of a stentgraft is affected by the stresses and hemodynamic forces applied to it, and may be reflected by the movements of the stentgraft itself during the cardiac cycle. A conventional CT scan (which results in a 3D volume) is not able to visualize these movements. However, applying ECG-gating does provide insight in the motion of the stentgraft caused by hemodynamic forces at different phases of the cardiac cycle. The amount of data obtained is a factor of ten larger compared to conventional CT, but the radiation dose is kept similar for patient safety. This causes the data to be noisy, and streak artifacts are more common. Algorithms for automatic stentgraft detection must be able to cope with this. Segmentation of the stentgraft is performed by examining slices perpendicular to the centreline. Regions with high CT-values exist at the locations where the metallic frame penetrates the slice. These regions are well suited for detection and sub-pixel localization. Spurious points can be removed by means of a clustering algorithm, leaving only points on the contour of the stent. We compare the performance of several different point detection methods and clustering algorithms. The position of the stent’s centreline is calculated by fitting a circle through these points. The proposed method can detect several stentgraft types, and is robust against noise and streak artifacts.
Item Type:	Conference or Workshop Item
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:	Signals and Systems (SAS)
Link to this item:	http://purl.utwente.nl/publications/62225
Official URL:	http://dx.doi.org/10.1117/12.770064
Export this item as:	BibTeX EndNote HTML Citation Reference Manager

Show download statistics for this publication

Repository Staff Only: item control page

Metis ID: 250916