Atlas Encoding by Randomized Forests for Efficient Label Propagation

@article{Zikic2013AtlasEB,
  title={Atlas Encoding by Randomized Forests for Efficient Label Propagation},
  author={Darko Zikic and Ben Glocker and Antonio Criminisi},
  journal={Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention},
  year={2013},
  volume={16 Pt 3},
  pages={66-73}
}
We propose a method for multi-atlas label propagation based on encoding the individual atlases by randomized classification forests. Most current approaches perform a non-linear registration between all atlases and the target image, followed by a sophisticated fusion scheme. While these approaches can achieve high accuracy, in general they do so at high computational cost. This negatively affects the scalability to large databases and experimentation. To tackle this issue, we propose to use a… CONTINUE READING
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