Low-Rank Atlas Image Analyses in the Presence of Pathologies

@article{Liu2015LowRankAI,
  title={Low-Rank Atlas Image Analyses in the Presence of Pathologies},
  author={Xiaoxiao Liu and Marc Niethammer and Roland Kwitt and Nikhil Singh and Matt McCormick and Stephen R. Aylward},
  journal={IEEE Transactions on Medical Imaging},
  year={2015},
  volume={34},
  pages={2583-2591}
}
We present a common framework, for registering images to an atlas and for forming an unbiased atlas, that tolerates the presence of pathologies such as tumors and traumatic brain injury lesions. This common framework is particularly useful when a sufficient number of protocol-matched scans from healthy subjects cannot be easily acquired for atlas formation and when the pathologies in a patient cause large appearance changes. Our framework combines a low-rank-plus-sparse image decomposition… CONTINUE READING

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