Adapting model-based deep learning to multiple acquisition conditions: Ada-MoDL.

Journal: Magnetic resonance in medicine

Published Date: Jun 18, 2023

Abstract

PURPOSE: The aim of this work is to introduce a single model-based deep network that can provide high-quality reconstructions from undersampled parallel MRI data acquired with multiple sequences, acquisition settings, and field strengths.

Authors

Aniket Pramanik

Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa, USA.
Sampada Bhave

Canon Medical Research USA, Cleveland, OH, USA.
Saurav Sajib

Canon Medical Research USA Inc., Mayfield Village, Ohio, USA.
Samir D Sharma

Canon Medical Research USA Inc., Mayfield Village, Ohio, USA.
Mathews Jacob

Keywords

Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Neural Networks, Computer

External Resources

View on PubMed Access via DOI PubMed (37332189)

Adapting model-based deep learning to multiple acquisition conditions: Ada-MoDL.

Abstract

Authors

Keywords

External Resources

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