2D-3D registration of abdominal angiographic data is a difficult problem due to hard time constraints during the intervention, different vessel contrast in volume and image, and motion blur caused by breathing. We propose a novel method for aligning 2D Digitally Subtracted Angiograms (DSA) to Computed Tomography Angiography (CTA) volumes, which requires no user interaction Lntrainterventionally. In an iterative process, we link 2D segmentation and 2D-3D registration using a probability map, which creates a common feature space where outliers in 2D and 3D are discarded consequently, Unlike other approaches, we keep user interaction low while high capture range and robustness against vessel variability and deformation are maintained, Tests on five patient data sets and a comparison to two recently proposed methods show the good performance of our method. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Groher, M., Bender, F., Hoffmann, R. T., & Navab, N. (2007). Segmentation-driven 2D-3D registration for abdominal catheter interventions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4792 LNCS, pp. 527–535). Springer Verlag. https://doi.org/10.1007/978-3-540-75759-7_64
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