• Corpus ID: 221104020

Using convolution neural networks to learn enhanced fiber orientation distribution models from commercially available diffusion magnetic resonance imaging

  title={Using convolution neural networks to learn enhanced fiber orientation distribution models from commercially available diffusion magnetic resonance imaging},
  author={Oeslle Lucena and Sjoerd B. Vos and Vejay Niranjan Vakharia and John S. Duncan and Keyoumars Ashkan and Rachel Sparks and S{\'e}bastien Ourselin},
Accurate local fiber orientation distribution (FOD) modeling based on diffusion magnetic resonance imaging (dMRI) capable of resolving complex fiber configurations benefit from specific acquisition protocols that impose a high number of gradient directions (b-vecs), a high maximum b-value (b-vals) and multiple b-values (multi-shell). However, acquisition time is limited in a clinical setting and commercial scanners may not provide robust state-of-the-art dMRI sequences. Therefore, dMRI is often… 

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