Improved compressed sensing and super-resolution of cardiac diffusion MRI with structure-guided total variation.
Irvin TehDarryl McClymontEric D CarruthJeffrey OmensAndrew D McCullochJurgen E SchneiderPublished in: Magnetic resonance in medicine (2020)
Acquiring one fully sampled non-diffusion-weighted image and 10 diffusion-weighted images at 8× undersampling would result in an 80% net reduction in data needed. We demonstrate efficacy of the DTV algorithm over TV in reducing data sampling requirements, which can be translated into higher apparent resolution and potentially shorter scan times. This method would be equally applicable in diffusion MRI applications outside the heart.
Keyphrases
- diffusion weighted
- contrast enhanced
- diffusion weighted imaging
- computed tomography
- magnetic resonance imaging
- deep learning
- magnetic resonance
- electronic health record
- big data
- machine learning
- dual energy
- heart failure
- convolutional neural network
- left ventricular
- atrial fibrillation
- optical coherence tomography
- single molecule
- data analysis