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Enhancing quality and speed in database-free neural network reconstructions of undersampled MRI with SCAMPI.

Thomas M SiedlerPeter M JakobVolker Herold
Published in: Magnetic resonance in medicine (2024)
Our approach avoids overfitting to dataset features, that can occur in Neural Networks trained on databases, because the network parameters are tuned only on the reconstruction data. It allows better results and faster reconstruction than the baseline untrained Neural Network approach.
Keyphrases
  • neural network
  • resistance training
  • big data
  • magnetic resonance imaging
  • contrast enhanced
  • electronic health record
  • body composition
  • quality improvement
  • computed tomography
  • high intensity
  • artificial intelligence