29 April 2005 Bi-temporal 3D active appearance models with applications to unsupervised ejection fraction estimation
Author Affiliations +
Abstract
Rapid and unsupervised quantitative analysis is of utmost importance to ensure clinical acceptance of many examinations using cardiac magnetic resonance imaging (MRI). We present a framework that aims at fulfilling these goals for the application of left ventricular ejection fraction estimation in four-dimensional MRI. The theoretical foundation of our work is the generative two-dimensional Active Appearance Models by Cootes et al., here extended to bi-temporal, three-dimensional models. Further issues treated include correction of respiratory induced slice displacements, systole detection, and a texture model pruning strategy. Cross-validation carried out on clinical-quality scans of twelve volunteers indicates that ejection fraction and cardiac blood pool volumes can be estimated automatically and rapidly with accuracy on par with typical inter-observer variability.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mikkel B. Stegmann, Mikkel B. Stegmann, Dorthe Pedersen, Dorthe Pedersen, } "Bi-temporal 3D active appearance models with applications to unsupervised ejection fraction estimation", Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); doi: 10.1117/12.594930; https://doi.org/10.1117/12.594930
PROCEEDINGS
15 PAGES


SHARE
Back to Top