Fully Automatic Segmentation of the Prostate using Active Appearance Models

@inproceedings{Vincent2012FullyAS,
  title={Fully Automatic Segmentation of the Prostate using Active Appearance Models},
  author={Gregoire Vincent and Gwenael Guillard and Mike Bowes},
  year={2012}
}
We present a fully automatic model based system for segmenting the prostate in magnetic resonance (MR) images. The segmentation method is based on Active Appearance Models (AAM) built from manually segmented examples provided by the MICCAI 2012 Promise12 team. High quality correspondences for the model are generated using a Minimum Description Length (MDL) Groupwise Image Registration method. A multi start optimisation scheme is used to robustly match the model to new images. The model has been… CONTINUE READING
Highly Cited
This paper has 57 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 24 extracted citations

57 Citations

01020'13'14'15'16'17'18
Citations per Year
Semantic Scholar estimates that this publication has 57 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 12 references

Automated Segmentation of the Prostate in 3D MR Images Using a Probabilistic Atlas and a Spatially Constrained Deformable Model

  • Sébastien Martin, Vincent Daanen, Jocelyne Troccaz
  • Medical Physics,
  • 2010
2 Excerpts

Fully automatic segmentation of the knee joint using active appearance models

  • Graham Vincent, Chris Wolstenholme, Ian Scott, Mike Bowes
  • Proceedings of MICCAI
  • 2010
1 Excerpt

Prostate Pathology

  • Pete A. Humphrey
  • American Society for Clinical Pathology.,
  • 2003
1 Excerpt

Similar Papers

Loading similar papers…