Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
A fast level set method for propagating interfaces
Journal of Computational Physics
International Journal of Computer Vision
A new model for the recovery of cylindrical structures from medical image data
CVRMed-MRCAS '97 Proceedings of the First Joint Conference on Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery
Efficient and reliable schemes for nonlinear diffusion filtering
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Predictive Simulation of Bidirectional Glenn Shunt Using a Hybrid Blood Vessel Model
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
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As interventional magnetic resonance imaging (iMRI) is getting closer to clinical practice, new means of visualization and navigation are required. We present an approach to create a virtual endoscopic view inside the human aorta in real-time. In our approach, defined cross-sectional slices are acquired and segmented in a highly optimized fashion. A geometric shape model is fit to the segmentation points and continuously updated during the intervention. The physician can then view and navigate inside the structure to plan the intervention and get immediate feedback about the procedure. As a component of this system, this work focuses on the segmentation of the cross-sectional images and the fitting of the shape model. We present a real-time 2D segmentation implementation for this application domain and a model fitting scheme for a generalized cylinder (GC) model. For the latter we employ a new scheme for choosing the local reference frame.