Cardiac Motion Analysis from Ultrasound Sequences Using Non-rigid Registration
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Separating Style and Content with Bilinear Models
Neural Computation
Bilinear Models for Spatio-Temporal Point Distribution Analysis
International Journal of Computer Vision
Model based cardiac motion tracking using velocity encoded magnetic resonance imaging
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Bilinear Models for 3-D Face and Facial Expression Recognition
IEEE Transactions on Information Forensics and Security
Atlas construction and image analysis using statistical cardiac models
STACOM'10/CESC'10 Proceedings of the First international conference on Statistical atlases and computational models of the heart, and international conference on Cardiac electrophysiological simulation challenge
Hi-index | 0.00 |
This paper presents a cardiac motion modeling method that separates motion from anatomical patient specific cardiac features by using bilinear models on segmented heart volumes. This factoring in a quasi-independent anatomy-motion transform significantly reduces the dimensionality of the data to analyze: instead of having to check all the points on the volumetric mesh, we analyze a reduced number of parameters corresponding to the shape variation induced by motion. Bilinear models are first learnt in a large population of subjects, and then applied individually to each subject to derive a patient specific model. This provides information about individual specific motion parameters, facilitating the detection of individuals that are far from the mean cardiac motion pattern and motion interpolation.