Multiple Mean Models of Statistical Shape and Probability Priors for Automatic Prostate Segmentation

@inproceedings{Ghose2011MultipleMM,
  title={Multiple Mean Models of Statistical Shape and Probability Priors for Automatic Prostate Segmentation},
  author={Soumya Ghose and Arnau Oliver and Robert M Marti and Xavier Llad{\'o} and Jordi Freixenet and Jhimli Mitra and Joan Carles Vilanova and Josep Comet and Fabrice M{\'e}riaudeau},
  booktitle={Prostate Cancer Imaging},
  year={2011}
}
Low contrast of the prostate gland, heterogeneous intensity distribution inside the prostate region, imaging artifacts like shadow regions, speckle and significant variations in prostate shape, size and inter dataset contrast in Trans Rectal Ultrasound (TRUS) images challenge computer aided automatic or semi-automatic segmentation of the prostate. In this paper, we propose a probabilistic framework for automatic initialization and propagation of multiple mean parametric models derived from… CONTINUE READING

Citations

Publications citing this paper.
Showing 1-10 of 12 extracted citations

A Mumford-Shah functional based variational model with contour, shape, and probability prior information for prostate segmentation

Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012) • 2012
View 2 Excerpts

References

Publications referenced by this paper.
Showing 1-10 of 15 references

Prostate boundary segmentation from 2D ultrasound images.

Medical physics • 2000
View 5 Excerpts
Highly Influenced

2009 prostate segmentation challenge MICCAI

MICCAI
http://wiki.namic.org/Wiki/index.php, accessed on [1st April, 2011] • 2009
View 2 Excerpts

Similar Papers

Loading similar papers…