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MICCAI
2006
Springer

Boosting and Nonparametric Based Tracking of Tagged MRI Cardiac Boundaries

13 years 15 days ago
Boosting and Nonparametric Based Tracking of Tagged MRI Cardiac Boundaries
Abstract. In this paper we present an accurate cardiac boundary tracking method for 2D tagged MRI time sequences. This method naturally integrates the motion and the static local appearance features and generates accurate boundary criteria via a boosting approach. We extend the conventional Adaboost classifier into a posterior probability form, which can be embedded in a particle filtering-based shape tracking framework. To make the tracking process more robust and faster, we use a PCA subspace shape representation to constrain the shape variation and lower the dimensionality. We also learn two shape-dynamic models for systole and diastole separately, to predict the shape evolution. Our tracking method incorporates the static appearance, the motion appearance, the shape constraints, and the dynamic prediction in a unified way. The proposed method has been implemented on 50 tagged MRI sequences. The experimental results show the accuracy and robustness of our approach.
Zhen Qian, Dimitris N. Metaxas, Leon Axel
Added 14 Nov 2009
Updated 14 Nov 2009
Type Conference
Year 2006
Where MICCAI
Authors Zhen Qian, Dimitris N. Metaxas, Leon Axel
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