AI in MRI: Computational Frameworks for a Faster, Optimized, and Automated Imaging Workflow

Efrat Shimron; Or Perlman

doi:10.3390/bioengineering10040492

AI in MRI: Computational Frameworks for a Faster, Optimized, and Automated Imaging Workflow

Bioengineering (Basel). 2023 Apr 20;10(4):492. doi: 10.3390/bioengineering10040492.

Authors

Efrat Shimron¹, Or Perlman^{2

3}

Affiliations

¹ Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA.
² Department of Biomedical Engineering, Tel Aviv University, Tel Aviv 6997801, Israel.
³ Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 6997801, Israel.

Abstract

Over the last decade, artificial intelligence (AI) has made an enormous impact on a wide range of fields, including science, engineering, informatics, finance, and transportation [...].

Keywords: acceleration; artificial intelligence (AI); deep learning; image reconstruction; machine learning; magnetic resonance imaging (MRI); medical imaging; segmentation.

Publication types

Editorial

Grants and funding

This work was supported by the Ministry of Innovation, Science and Technology, Israel, the Weizmann Institute Women’s Postdoctoral Career Development Award in Science, and a grant from the Tel Aviv University Center for AI and Data Science (TAD).