Automatic Segmentation of a Fetal Echocardiogram Using Modified Active Appearance Models and Sparse Representation

@article{Guo2014AutomaticSO,
  title={Automatic Segmentation of a Fetal Echocardiogram Using Modified Active Appearance Models and Sparse Representation},
  author={Yi Guo and Yuanyuan Wang and Siqing Nie and Jinhua Yu and Ping Chen},
  journal={IEEE Transactions on Biomedical Engineering},
  year={2014},
  volume={61},
  pages={1121-1133}
}
A novel approach is presented to automatically segment the left ventricle in fetal echocardiograms. The proposed approach strategically integrates sparse representation, global constraint, and local refinement algorithms into an active appearance model (AAM) framework. In the training stage, we construct an enhanced AAM texture model to deal with the speckle and texture ambiguities. In the segmentation stage, the initial pose is located by a sparse representation method. Globally constrained… CONTINUE READING
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