Journal article
Multi-view active appearance models for consistent segmentation of multiple standard views: application to long- and short-axis cardiac MR images
International Congress series, Vol.1256(C), pp.1141-1146
2003
DOI: 10.1016/S0531-5131(03)00470-9
Abstract
This paper describes a multi-view Active Appearance Model (AAM) for coherent segmentation of multiple cardiac views. Cootes' AAM framework was adapted by considering shapes and intensities from multiple views as single shape and intensity samples, while eliminating trivial difference in object pose in different views. This way, the coherence in organ shape and intensities between different views is modeled and utilized during image search. In a leave-one-out validation study on a combination of four-chamber, two-chamber and short-axis cardiac MR views from 29 patients, low border positioning errors were found comparing manual and computer detected borders, whereas no statistically significant difference in contour area was present. The presented validation shows that the method combines a high robustness with clinically acceptable accuracy, and therefore is a promising tool to further automate the integral quantitative analysis of cardiac MR patient examinations.
Details
- Title: Subtitle
- Multi-view active appearance models for consistent segmentation of multiple standard views: application to long- and short-axis cardiac MR images
- Creators
- B.P.F Lelieveldt - Leiden University Medical CenterM Üzümcü - Leiden University Medical CenterR.J van der Geest - Leiden University Medical CenterJ.H.C Reiber - Leiden University Medical CenterM Sonka - University of Iowa
- Resource Type
- Journal article
- Publication Details
- International Congress series, Vol.1256(C), pp.1141-1146
- DOI
- 10.1016/S0531-5131(03)00470-9
- ISSN
- 0531-5131
- eISSN
- 1873-6157
- Publisher
- Elsevier B.V
- Language
- English
- Date published
- 2003
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Radiation Oncology; Fraternal Order of Eagles Diabetes Research Center; Injury Prevention Research Center; Ophthalmology and Visual Sciences
- Record Identifier
- 9984186602402771
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