Least median of squares filtering of locally optimal point matches for compressible flow image registration.

@article{Castillo2012LeastMO,
  title={Least median of squares filtering of locally optimal point matches for compressible flow image registration.},
  author={Edward Castillo and Richard Castillo and Benjamin White and Javier Rojo and Thomas Guerrero},
  journal={Physics in medicine and biology},
  year={2012},
  volume={57 15},
  pages={4827-33}
}
Compressible flow based image registration operates under the assumption that the mass of the imaged material is conserved from one image to the next. Depending on how the mass conservation assumption is modeled, the performance of existing compressible flow methods is limited by factors such as image quality, noise, large magnitude voxel displacements, and computational requirements. The Least Median of Squares Filtered Compressible Flow (LFC) method introduced here is based on a localized… CONTINUE READING