Bayesian Principal Geodesic Analysis in Diffeomorphic Image Registration

@article{Zhang2014BayesianPG,
  title={Bayesian Principal Geodesic Analysis in Diffeomorphic Image Registration},
  author={Miaomiao Zhang and P. Thomas Fletcher},
  journal={Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention},
  year={2014},
  volume={17 Pt 3},
  pages={
          121-8
        }
}
Computing a concise representation of the anatomical variability found in large sets of images is an important first step in many statistical shape analyses. In this paper, we present a generative Bayesian approach for automatic dimensionality reduction of shape variability represented through diffeomorphic mappings. To achieve this, we develop a latent variable model for principal geodesic analysis (PGA) that provides a probabilistic framework for factor analysis on diffeomorphisms. Our key… CONTINUE READING
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Bayesian PCA

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  • Advances in neural information processing systems…
  • 1999
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