An end‐to‐end AI‐based framework for automated discovery of rapid CEST/MT MRI acquisition protocols and molecular parameter quantification (AutoCEST)-Reference-Cited by-同舟云学术

An end‐to‐end AI‐based framework for automated discovery of rapid CEST/MT MRI acquisition protocols and molecular parameter quantification (AutoCEST)

Published:2022-01-28 Issue:6 Volume:87 Page:2792-2810
ISSN:0740-3194
Container-title:Magnetic Resonance in Medicine
language:en
Short-container-title:Magnetic Resonance in Med

Author:

Perlman Or¹^ORCID,Zhu Bo¹,Zaiss Moritz²³^ORCID,Rosen Matthew S.¹⁴^ORCID,Farrar Christian T.¹^ORCID

Affiliation:

1. Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology Massachusetts General Hospital and Harvard Medical School Charlestown MA USA

2. Magnetic Resonance Center Max Planck Institute For Biological Cybernetics Tübingen Germany

3. Department of Neuroradiology University Hospital Erlangen Friedrich‐Alexander‐Universität Erlangen‐Nürnberg (FAU) Erlangen Germany

4. Department of Physics Harvard University Cambridge MA USA

Funder

National Institutes of Health

National Cancer Institute

H2020 Marie Skłodowska-Curie Actions

Publisher

Wiley

Subject

Radiology, Nuclear Medicine and imaging

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrm.29173

Reference64 articles.

1. A New Class of Contrast Agents for MRI Based on Proton Chemical Exchange Dependent Saturation Transfer (CEST)

2. Clinical applications of chemical exchange saturation transfer (CEST) MRI

3. Magnetization Transfer Contrast and Chemical Exchange Saturation Transfer MRI. Features and analysis of the field-dependent saturation spectrum

4. APT-weighted MRI: Techniques, current neuro applications, and challenging issues

5. Detection of the Ischemic Penumbra Using pH-Weighted MRI

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