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BILDMED
2007

Bayesian Vessel Extraction for Planning of Radiofrequency-Ablation

8 years 10 months ago
Bayesian Vessel Extraction for Planning of Radiofrequency-Ablation
The software-assisted planning of radiofrequency-ablation of liver tumors calls for robust and fast methods to segment the tumor and surrounding vascular structures from clinical data to allow a numerical estimation, whether a complete thermal destruction of the tumor is feasible taking the cooling effect of the vessels into account. As the clinical workflow in radiofrequency-ablation does not allow for time consuming planning procedures, the implementation of robust and fast segmentation algorithms is critical in building a streamlined software application tailored to the clinical needs. To suppress typical artifacts in clinical CT or MRT data - like inhomogeneous background density due to the imaging procedure - a Bayesian background compensation is developed, which subsequently allows a robust segmentation of the vessels by fast threshold based algorithms. The presented Bayesian background compensation has proven to handle a wide range of image perturbances in MRT and CT data and ...
Stephan Zidowitz, Johann Drexl, Tim Kröger, T
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where BILDMED
Authors Stephan Zidowitz, Johann Drexl, Tim Kröger, Tobias Preusser, Felix Ritter, Andreas Weihusen, Heinz-Otto Peitgen
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