Motion Analysis of the Right Ventricle From MRI Images
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Robust Real-Time Face Detection
International Journal of Computer Vision
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Automatic cardiac MRI segmentation using a biventricular deformable medial model
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part I
Automatic segmentation of the myocardium in cine MR images using deformable registration
STACOM'11 Proceedings of the Second international conference on Statistical Atlases and Computational Models of the Heart: imaging and modelling challenges
Layered spatio-temporal forests for left ventricle segmentation from 4d cardiac MRI data
STACOM'11 Proceedings of the Second international conference on Statistical Atlases and Computational Models of the Heart: imaging and modelling challenges
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Cardiac magnetic resonance imaging (MRI) has advanced to become a powerful tool in clinical practice. Extraction of morphological and functional features from cardiac MR imaging for diagnosis and disease monitoring remains a time-consuming task for clinicians. We present a fully automatic approach to extracting the structures and dynamics for both left and right ventricles. The cine short-axis stack of a cardiac MR scan is used to reconstruct a 3D volume sequence. A joint LV-RV model is introduced to delineate the boundaries of both left and right ventricles in each frame, and to combine both spatial and temporal context to track the chamber boundary motion over cardiac cycles. Both qualitative and quantitative results show promise of the proposed method.