Adversarial Learning for MRI Reconstruction and Classification of Cognitively Impaired Individuals-Reference-Cited by-同舟云学术

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Adversarial Learning for MRI Reconstruction and Classification of Cognitively Impaired Individuals

Published:2024 Issue: Volume:12 Page:83169-83182
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Zhou Xiao¹,Balachandra Akshara R.²^ORCID,Romano Michael F.³,Peter Chin Sang¹,Au Rhoda⁴^ORCID,Kolachalama Vijaya B.³^ORCID

Affiliation:

1. Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA

2. Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA

3. Department of Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA

4. Department of Anatomy and Neurobiology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA

Funder

Karen Toffler Charitable Trust, the National Institute of Diabetes and Digestive and Kidney Diseases Diabetic Complications Consortium

Strategically Focused Research Network (SFRN) Center from the American Heart Association

National Institutes of Health

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10546982.pdf?arnumber=10546982

Reference47 articles.

1. Neuroimaging advances regarding subjective cognitive decline in preclinical Alzheimer’s disease

2. Comparing 3T and 1.5T MRI for Mapping Hippocampal Atrophy in the Alzheimer's Disease Neuroimaging Initiative (ADNI) (P06.029)

3. Image reconstruction: An overview for clinicians

4. DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction

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