Corpus ID: 6370749

Automatic 3D Liver Segmentation Using Sparse Representation of Global and Local Image Information via Level Set Formulation

@article{AlShaikhli2015Automatic3L,
  title={Automatic 3D Liver Segmentation Using Sparse Representation of Global and Local Image Information via Level Set Formulation},
  author={Saif Dawood Salman Al-Shaikhli and M. Yang and B. Rosenhahn},
  journal={ArXiv},
  year={2015},
  volume={abs/1508.01521}
}
In this paper, a novel framework for automated liver segmentation via a level set formulation is presented. A sparse representation of both global (region-based) and local (voxel-wise) image information is embedded in a level set formulation to innovate a new cost function. Two dictionaries are build: A region-based feature dictionary and a voxel-wise dictionary. These dictionaries are learned, using the K-SVD method, from a public database of liver segmentation challenge (MICCAI-SLiver07). The… Expand
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