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Versatile, robust, and efficient tractography with constrained higher-order tensor fODFs.

Michael AnkeleLek-Heng LimSamuel GroeschelThomas Schultz
Published in: International journal of computer assisted radiology and surgery (2017)
The proposed method works faster than state-of-the-art approaches, achieves higher angular resolution on simulated data with known ground truth, and plausible results on clinical data. In addition to working with the same data as previous methods for multi-tissue deconvolution, it also supports DSI data.
Keyphrases
  • electronic health record
  • big data
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  • machine learning
  • multiple sclerosis
  • white matter
  • deep learning