Accelerating multi-echo chemical shift encoded water-fat MRI using model-guided deep learning.
Shuo LiChenfei ShenZekang DingHuajun SheYiping P DuPublished in: Magnetic resonance in medicine (2022)
The proposed MGDL-WF enables exploiting features of the water images and fat images from the undersampled multi-echo data, leading to improved performance in the accelerated CSE water-fat imaging. By using MGDL-WF, radial sampling can further improve the image quality with comparable scan time in comparison with Cartesian sampling.
Keyphrases
- deep learning
- image quality
- adipose tissue
- convolutional neural network
- contrast enhanced
- computed tomography
- diffusion weighted imaging
- magnetic resonance
- magnetic resonance imaging
- fatty acid
- artificial intelligence
- high resolution
- optical coherence tomography
- electronic health record
- dual energy
- ultrasound guided