Classification of Myocardial 18F-FDG PET Uptake Patterns Using Deep Learning-Reference-Cited by-同舟云学术

Classification of Myocardial 18F-FDG PET Uptake Patterns Using Deep Learning

Published:2021-07-01 Issue:4 Volume:3 Page:e200148
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Josselyn Nicholas¹,MacLean Matthew T.¹,Jean Christopher¹,Fuchs Ben¹^ORCID,Moon Brianna F.¹^ORCID,Hwuang Eileen¹^ORCID,Iyer Srikant Kamesh¹,Litt Harold¹^ORCID,Han Yuchi¹^ORCID,Kaghazchi Fatemeh¹,Bravo Paco E.¹,Witschey Walter R.¹^ORCID

Affiliation:

1. From the Departments of Radiology (N.J., M.T.M., C.J., B.F., H.L., Y.H., F.K., P.E.B., W.R.W.), Bioengineering (B.F.M., E.H., S.K.I.), and Medicine (Y.H., P.B.), Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, South Pavilion, Room 11-155, Philadelphia, PA 19104.

Publisher

Radiological Society of North America (RSNA)

Subject

General Medicine

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryai.2021200148

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2. Relationship Between Carbohydrate and Lipid Metabolism and the Energy Balance of Heart Muscle

3. Presurgical identification of hibernating myocardium by combined use of technetium-99m hexakis 2-methoxyisobutylisonitrile single photon emission tomography and fluorine-18 fluoro-2-deoxy-d-glucose positron emission tomography in patients with coronary artery disease

4. Myocardial glucose metabolism in patients with hypertrophic cardiomyopathy: Assessment by F-18-FDG PET study

5. Incidental focal FDG uptake in heart is a lighthouse for considering cardiac screening

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