SIAM Review
Muliscale Vessel Enhancement Filtering
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Automatic Centerline Extraction for 3D Virtual Bronchoscopy
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
An Adaptive Minimal Path Generation Technique for Vessel Tracking in CTA/CE-MRA Volume Images
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
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
Minimum Cost Path Determination Using a Simple Heuristic Function
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Comparison of vessel segmentations using STAPLE
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
Geodesic voting for the automatic extraction of tree structures. Methods and applications
Computer Vision and Image Understanding
Hi-index | 0.00 |
A method is presented that aims at finding the central vessel axis in two and three dimensional angiographic images based on a single user defined point. After the vessels in the image are enhanced using a special purpose filter, the operator is asked to point out the vessel of interest. Subsequently, a wave front propagation is started based on the response of the filter. By analyzing the evolution of the wave front, points are retrieved that are very likely to be part of the vessel of interest. These points can either be combined to form a connected structure or to retrieve the minimum cost path to the user defined point. In this paper examples of this approach are given that illustrate the performance of this method in different types of images and in situations where there is no or hardly any image evidence of the vessel at hand.