Bi-temporal 3D active appearance models with applications to unsupervised ejection fraction estimation |
Mikkel B. Stegmann, Dorthe Pedersen
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| 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. |
| Type | Conference paper [With referee] |
| Conference | International Symposium on Medical Imaging 2005, San Diego, CA, Proc. of SPIE |
| Year | 2005 Month February Vol. 5747 pp. 336-350 |
| Publisher | SPIE |
| Electronic version(s) | [pdf] |
| BibTeX data | [bibtex] |
| IMM Group(s) | Image Analysis & Computer Graphics |