Landmark-based segmentation of lungs while handling partial correspondences using sparse graph-based priors

@article{Besbes2011LandmarkbasedSO,
  title={Landmark-based segmentation of lungs while handling partial correspondences using sparse graph-based priors},
  author={Ahmed Besbes and Nikos Paragios},
  journal={2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro},
  year={2011},
  pages={989-995}
}
In this paper, we propose a new segmentation algorithm that combines a graph-based shape model with image cues based on boosted features. The landmark-based shape model encodes prior constraints through the normalized Euclidean distances between pairs of control points, alleviating the need of a large database for the training. Moreover, the graph topology is deduced from the dataset using manifold learning and unsupervised clustering. In a graph-matching-like manner, we formulate the… CONTINUE READING
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