Improved inference in Bayesian segmentation using Monte Carlo sampling: Application to hippocampal subfield volumetry

@article{Iglesias2013ImprovedII,
  title={Improved inference in Bayesian segmentation using Monte Carlo sampling: Application to hippocampal subfield volumetry},
  author={Juan Eugenio Iglesias and Mert R. Sabuncu and Koenraad Van Leemput},
  journal={Medical image analysis},
  year={2013},
  volume={17 7},
  pages={766-78}
}
Many segmentation algorithms in medical image analysis use Bayesian modeling to augment local image appearance with prior anatomical knowledge. Such methods often contain a large number of free parameters that are first estimated and then kept fixed during the actual segmentation process. However, a faithful Bayesian analysis would marginalize over such parameters, accounting for their uncertainty by considering all possible values they may take. Here we propose to incorporate this uncertainty… CONTINUE READING

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