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This paper describes a new approach to the automated segmentation of X-ray left ventricular (LV) angiograms, based on active appearance models (AAMs) and dynamic programming. A coupling of shape and texture information between the end-diastolic (ED) and end-systolic (ES) frame was achieved by constructing a multiview AAM. Over-constraining of the model was(More)
This paper presents a novel conditional statistical shape model in which the condition can be relaxed instead of being treated as a hard constraint. The major contribution of this paper is the integration of an error model that estimates the reliability of the observed conditional features and subsequently relaxes the conditional statistical shape model(More)
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, while eliminating trivial difference in object pose in different views. This way, the coherence in organ shape and intensities between different(More)
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