Semi-automatic level set segmentation of liver tumors combining a spiral-scanning technique with supervised fuzzy pixel classification

@article{Smeets2010SemiautomaticLS,
  title={Semi-automatic level set segmentation of liver tumors combining a spiral-scanning technique with supervised fuzzy pixel classification},
  author={Dirk Smeets and Dirk Loeckx and Bert Stijnen and Bart De Dobbelaer and Dirk Vandermeulen and Paul Suetens},
  journal={Medical image analysis},
  year={2010},
  volume={14 1},
  pages={
          13-20
        }
}
In this paper, a specific method is presented to facilitate the semi-automatic segmentation of liver tumors and liver metastases in CT images. Accurate and reliable segmentation of tumors is essential for the follow-up of cancer treatment. The core of the algorithm is a level set method. The initialization is generated by a spiral-scanning technique based on dynamic programming. The level set evolves according to a speed image that is the result of a statistical pixel classification algorithm… CONTINUE READING

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