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Coupled Registration-Segmentation: Application to Femur Analysis with Intra-subject Multiple Levels of Detail MRI Data

Schmid, J. and Kim, J. and Magnenat-Thalmann, N.


Abstract: The acquisition of intra-subject data from multiple images is routinely performed to provide complementary information where a single image is not sufficient. However, these images are not always coregistered since they are acquired with different scanners, affected by subject’s movements during scans, and consist of different image attributes such as field of view (FOV) or intensities distribution. In this study, we propose a coupled registration-segmentation framework that simultaneously registers and segments intra-subject images with different characteristics (e.g. image resolution and FOV). The proposed coupled framework is demonstrated with the processing of multiple level of detail (LOD) Magnetic Resonance Imaging (MRI) acquisitions of the hip joint components, which yield efficient and automated approaches to analyze soft tissues (from high-resolution MRI) in conjunction with the entire hip joint structures (from low resolution MRI).


@inproceedings{562,
  booktitle = {MICCAI},
  author = {Schmid, J. and Kim, J. and Magnenat-Thalmann, N.},
  title = {Coupled Registration-Segmentation: Application to Femur Analysis with Intra-subject Multiple Levels of Detail MRI Data},
  publisher = {Springer},
  volume = {LNCS vol.6362},
  pages = {562-569},
  month = sep,
  year = {2010},
  topic = {Medical}
}