Detection and visualization of endoleaks in CT data for monitoring of thoracic and abdominal aortic aneurysm stents

J. Lu; J. Egger; A. Wimmer; S. Großkopf; B. Freisleben

doi:10.1117/12.769414

17 March 2008 Detection and visualization of endoleaks in CT data for monitoring of thoracic and abdominal aortic aneurysm stents

J. Lu, J. Egger, A. Wimmer, S. Großkopf, B. Freisleben

Author Affiliations +

Proceedings Volume 6918, Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling; 69181F (2008) https://doi.org/10.1117/12.769414
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

In this paper we present an efficient algorithm for the segmentation of the inner and outer boundary of thoratic and abdominal aortic aneurysms (TAA & AAA) in computed tomography angiography (CTA) acquisitions. The aneurysm segmentation includes two steps: first, the inner boundary is segmented based on a grey level model with two thresholds; then, an adapted active contour model approach is applied to the more complicated outer boundary segmentation, with its initialization based on the available inner boundary segmentation. An opacity image, which aims at enhancing important features while reducing spurious structures, is calculated from the CTA images and employed to guide the deformation of the model. In addition, the active contour model is extended by a constraint force that prevents intersections of the inner and outer boundary and keeps the outer boundary at a distance, given by the thrombus thickness, to the inner boundary. Based upon the segmentation results, we can measure the aneurysm size at each centerline point on the centerline orthogonal multiplanar reformatting (MPR) plane. Furthermore, a 3D TAA or AAA model is reconstructed from the set of segmented contours, and the presence of endoleaks is detected and highlighted. The implemented method has been evaluated on nine clinical CTA data sets with variations in anatomy and location of the pathology and has shown promising results.

Citation Download Citation

J. Lu, J. Egger, A. Wimmer, S. Großkopf, and B. Freisleben "Detection and visualization of endoleaks in CT data for monitoring of thoracic and abdominal aortic aneurysm stents", Proc. SPIE 6918, Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling, 69181F (17 March 2008); https://doi.org/10.1117/12.769414

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