Mean value coordinates for closed triangular meshes
ACM SIGGRAPH 2005 Papers
Harmonic coordinates for character articulation
ACM SIGGRAPH 2007 papers
ACM SIGGRAPH 2008 papers
Computer Aided Geometric Design - Special issue: Geometric modelling and differential geometry
Spline-Based probabilistic model for anatomical landmark detection
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Automatic segmentation of the pelvic bones from CT data based on a statistical shape model
EG VCBM'08 Proceedings of the First Eurographics conference on Visual Computing for Biomedicine
| Hi-index | 0.00 |
This work presents three different methods for automatic detection of anatomical landmarks in CT data, namely for the left and right anterior superior iliac spines and the pubic symphysis. The methods exhibit different degrees of generality in terms of portability to other anatomical landmarks and require a different amount of training data. The first method is problem-specific and is based on the convex hull of the pelvis. Method two is a more generic approach based on a statistical shape model including the landmarks of interest for every training shape. With our third method we present the most generic approach, where only a small set of training landmarks is required. Those landmarks are transferred to the patient specific geometry based on Mean Value Coordinates (MVCs). The methods work on surfaces of the pelvis that need to be extracted beforehand. We perform this geometry reconstruction with our previously introduced fully automatic segmentation framework for the pelvic bones. With a focus on the accuracy of our novel MVC-based approach, we evaluate and compare our methods on 100 clinical CT datasets, for which gold standard landmarks were defined manually by multiple observers.