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 fourdimensional 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 an accuracy on par with typical inter-observer variability.
|Title of host publication||IAVP - Image Analysis in Vivo Pharmachology, Roskilde, Denmark|
|Publication status||Published - 2005|
|Event||IAVP - Image Analysis in Vivo Pharmachology, Roskilde, Denmark - |
Duration: 1 Jan 2005 → …
|Conference||IAVP - Image Analysis in Vivo Pharmachology, Roskilde, Denmark|
|Period||01/01/2005 → …|