IEEE Transactions on Pattern Analysis and Machine Intelligence
A Variational Approach for the Segmentation of the Left Ventricle in Cardiac Image Analysis
International Journal of Computer Vision
Improving Performance of Distribution Tracking through Background Mismatch
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Segmentation of the Left Ventricle in Cardiac MR and CT Images
International Journal of Computer Vision
International Journal of Computer Vision
4D shape priors for a level set segmentation of the left myocardium in SPECT sequences
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Improving segmentation of the left ventricle using a two-component statistical model
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Segmenting and tracking the left ventricle by learning the dynamics in cardiac images
IPMI'05 Proceedings of the 19th international conference on Information Processing in Medical Imaging
Image Segmentation Using Active Contours Driven by the Bhattacharyya Gradient Flow
IEEE Transactions on Image Processing
Segmentation of Left Ventricle in Cardiac Cine MRI: An Automatic Image-Driven Method
FIMH '09 Proceedings of the 5th International Conference on Functional Imaging and Modeling of the Heart
Level Set Image Segmentation with a Statistical Overlap Constraint
IPMI '09 Proceedings of the 21st International Conference on Information Processing in Medical Imaging
Heart Motion Abnormality Detection via an Information Measure and Bayesian Filtering
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Pattern Recognition of Abnormal Left Ventricle Wall Motion in Cardiac MR
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Left Ventricle Segmentation via Graph Cut Distribution Matching
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Regional heart motion abnormality detection via information measures and unscented kalman filtering
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part I
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
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This study investigates overlap priorsfor tracking the Left Ventricle (LV) endo- and epicardium boundaries in cardiac Magnetic Resonance (MR) sequences. It consists of evolving two curves following the Euler-Lagrange minimization of two functionals each containing an original overlap prior constraint. The latter measures the conformity of the overlap between the nonparametric(kernel-based) intensity distributions within the three target regions---LV cavity, myocardium and background---to a prior learned from a given segmentation of the first frame. The Bhattacharyyacoefficient is used as an overlap measure. Different from existing intensity-driven constraints, the overlap priors do not assume implicitlythat the overlap between the distributions within different regions has to be minimal. Although neither shape priors nor curve coupling were used, quantitative evaluation showed that the results correlate well with independent manual segmentations and the method compares favorably with other recent methods. The overlap priors lead to a LV tracking which is more versatile than existing methods because the solution is not bounded to the shape/intensity characteristics of a training set. We also demonstrate experimentally that the used overlap measures are approximately constant over a cardiac sequence.