Locally Deformable Shape Model to Improve 3D Level Set Based Esophagus Segmentation

@article{Kurugol2010LocallyDS,
  title={Locally Deformable Shape Model to Improve 3D Level Set Based Esophagus Segmentation},
  author={Sila Kurugol and Necmiye Ozay and Jennifer G. Dy and Gregory C. Sharp and Dana H. Brooks},
  journal={2010 20th International Conference on Pattern Recognition},
  year={2010},
  pages={3955-3958}
}
In this paper we propose a supervised 3D segmentation algorithm to locate the esophagus in thoracic CT scans using a variational framework. To address challenges due to low contrast, several priors are learned from a training set of segmented images. Our algorithm first estimates the centerline based on a spatial model learned at a few manually marked anatomical reference points. Then an implicit shape model is learned by subtracting the centerline and applying PCA to these shapes. To allow… CONTINUE READING

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