Motion Analysis of Endovascular Stent-Grafts by MDL Based Registration
Abstract
The endovascular repair of a traumatic rupture of the thoracic aorta - that would otherwise lead to the death of the patient - is performed by delivering a stent-graft into the vessel at the rupture location. The age range of the affected patients is large and the stent-graft will stay in the body for the remaining life. The technique is relatively new, and no experience with regard to long-term effects, and durability exists. To predict long-term complications, such as ruptures or destructive interactions with surrounding tissue during the life of the patient, it is important to understand the - rather intense and constant - movement of the stent- graft during the cardiac cycle. A computed tomography with heart gating (gated CT) acquires sequences that show the region of the stent-graft at different time points. We analyze the motion of stent-grafts with a model based approach. Stent-grafts are represented as sparse sets of axis points extracted from the gated CT, and motion patterns are captured by a minimum description length based group-wise registration of the stent-graft at different time points. No parameterization or a priori definition of the topology is necessary, and highly variable elasticity properties in the data volume can by accounted for by the sparse statistical model, that captures correlations and motion components of the stent-graft. We report results for deformation models and registration accuracy for 5 patients.
Cite
Text
Langs et al. "Motion Analysis of Endovascular Stent-Grafts by MDL Based Registration." IEEE/CVF International Conference on Computer Vision, 2007. doi:10.1109/ICCV.2007.4409149Markdown
[Langs et al. "Motion Analysis of Endovascular Stent-Grafts by MDL Based Registration." IEEE/CVF International Conference on Computer Vision, 2007.](https://mlanthology.org/iccv/2007/langs2007iccv-motion/) doi:10.1109/ICCV.2007.4409149BibTeX
@inproceedings{langs2007iccv-motion,
title = {{Motion Analysis of Endovascular Stent-Grafts by MDL Based Registration}},
author = {Langs, Georg and Paragios, Nikos and Donner, Rene and Desgranges, Pascal and Rahmouni, Alain and Kobeiter, Hicham},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {2007},
pages = {1-8},
doi = {10.1109/ICCV.2007.4409149},
url = {https://mlanthology.org/iccv/2007/langs2007iccv-motion/}
}