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Diffusion MRI data analysis using brain segmentation from anatomical images synthesized from diffusion data by deep learning(DeepAnat)

Improving the accessibility of deep learning-based denoising for MRI using transfer learning and self-supervised learning

Integration of blip reversal with CAIPI sampling enables simultaneous correction of slice aliasing and distortion in 3D multi-slab diffusion MRI

Author:Ziyu Li  Karla Miller  Wenchuan Wu  

Session Type:Power Pitch  

Session Date:Tuesday, 10 May 2022  

Topic:Module 14: Image Reconstruction  

Session Name:Pitch: Image Reconstruction & Signal Models  

Program Number:0246  

Room Session:Power Pitch Theatre 2  

Institution:University of Oxford  

Integration of blip reversal with CAIPI sampling enables simultaneous correction of slice aliasing and distortion in 3D multi-slab diffusion MRI

Author:Ziyu Li  Karla Miller  Wenchuan Wu  

Session Type:Power Pitch Poster  

Session Date:Tuesday, 10 May 2022  

Topic:

Session Name:Poster: Image Reconstruction & Signal Models  

Program Number:0246  

Room Session:Power Pitch Theatre 2  

Institution:University of Oxford  

Quantifying the uncertainty of neural networks using Monte Carlo dropout
for safer and more accurate deep learning based quantitative MRI