Login / Signup

High fidelity deep learning-based MRI reconstruction with instance-wise discriminative feature matching loss.

Ke WangJonathan I TamirAlfredo De GoyenecheUri WollnerRafi BradaStella X YuMichael Lustig
Published in: Magnetic resonance in medicine (2022)
We present UFLoss, a patch-based unsupervised learned feature loss, which allows the training of DL-based reconstruction to obtain more detailed texture, finer features, and sharper edges with higher overall image quality under DL-based reconstruction frameworks. (Code available at: https://github.com/mikgroup/UFLoss).
Keyphrases
  • deep learning
  • image quality
  • machine learning
  • contrast enhanced
  • computed tomography
  • artificial intelligence
  • convolutional neural network
  • magnetic resonance imaging
  • dual energy