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European Journal of Nuclear Medicine and Molecular Imaging
|
October 4, 2022
Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images
Robert J H Miller, Ananya Singh, Yuka Otaki, et al.
European Journal of Nuclear Medicine and Molecular Imaging
|
September 12, 2015
Comparison of (18)F-fluorodeoxyglucose positron emission tomography (FDG PET) and cardiac magnetic resonance (CMR) in corticosteroid-naive patients with conduction system disease due to cardiac sarcoidosis
Hiroshi Ohira, David H Birnie, Elena Pena, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology
|
May 16, 2019
Upper reference limits of transient ischemic dilation ratio for different protocols on new-generation cadmium zinc telluride cameras: A report from REFINE SPECT registry
Lien-Hsin Hu, Tali Sharir, Robert J H Miller, et al.
European Journal of Nuclear Medicine and Molecular Imaging
|
April 17, 2023
Unsupervised learning to characterize patients with known coronary artery disease undergoing myocardial perfusion imaging
Michelle C Williams, Bryan P Bednarski, Konrad Pieszko, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology
|
July 6, 2021
Diagnostic safety of a machine learning-based automatic patient selection algorithm for stress-only myocardial perfusion SPECT
Evann Eisenberg, Robert J H Miller, Lien-Hsin Hu, et al.
JACC. Cardiovascular Imaging
|
March 7, 2023
Myocardial Perfusion PET for the Detection and Reporting of Coronary Microvascular Dysfunction: A JACC: Cardiovascular Imaging Expert Panel Statement
Thomas H Schindler, William F Fearon, Matthieu Pelletier-Galarneau, et al.
Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine
|
October 3, 2024
The Updated Registry of Fast Myocardial Perfusion Imaging with Next-Generation SPECT (REFINE SPECT 2.0)
Robert J H Miller, Mark Lemley, Aakash Shanbhag, et al.
Ebiomedicine
|
January 3, 2024
Clinical phenotypes among patients with normal cardiac perfusion using unsupervised learning: a retrospective observational study
Robert J H Miller, Bryan P Bednarski, Konrad Pieszko, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology
|
April 12, 2018
Correction to: Clinical Quantification of Myocardial Blood Flow Using PET: Joint Position Paper of the SNMMI Cardiovascular Council and the ASNC
Venkatesh L Murthy, Timothy M Bateman, Rob S Beanlands, et al.
Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine
|
December 16, 2017
Clinical Quantification of Myocardial Blood Flow Using PET: Joint Position Paper of the SNMMI Cardiovascular Council and the ASNC
Venkatesh L Murthy, Timothy M Bateman, Rob S Beanlands, et al.
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Search research articles
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Showing results (191-200 of 211) with videos related to
Sort By:
Page
of 22
European Journal of Nuclear Medicine and Molecular Imaging
|
October 4, 2022
Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images
Robert J H Miller, Ananya Singh, Yuka Otaki, et al.
European Journal of Nuclear Medicine and Molecular Imaging
|
September 12, 2015
Comparison of (18)F-fluorodeoxyglucose positron emission tomography (FDG PET) and cardiac magnetic resonance (CMR) in corticosteroid-naive patients with conduction system disease due to cardiac sarcoidosis
Hiroshi Ohira, David H Birnie, Elena Pena, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology
|
May 16, 2019
Upper reference limits of transient ischemic dilation ratio for different protocols on new-generation cadmium zinc telluride cameras: A report from REFINE SPECT registry
Lien-Hsin Hu, Tali Sharir, Robert J H Miller, et al.
European Journal of Nuclear Medicine and Molecular Imaging
|
April 17, 2023
Unsupervised learning to characterize patients with known coronary artery disease undergoing myocardial perfusion imaging
Michelle C Williams, Bryan P Bednarski, Konrad Pieszko, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology
|
July 6, 2021
Diagnostic safety of a machine learning-based automatic patient selection algorithm for stress-only myocardial perfusion SPECT
Evann Eisenberg, Robert J H Miller, Lien-Hsin Hu, et al.
JACC. Cardiovascular Imaging
|
March 7, 2023
Myocardial Perfusion PET for the Detection and Reporting of Coronary Microvascular Dysfunction: A JACC: Cardiovascular Imaging Expert Panel Statement
Thomas H Schindler, William F Fearon, Matthieu Pelletier-Galarneau, et al.
Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine
|
October 3, 2024
The Updated Registry of Fast Myocardial Perfusion Imaging with Next-Generation SPECT (REFINE SPECT 2.0)
Robert J H Miller, Mark Lemley, Aakash Shanbhag, et al.
Ebiomedicine
|
January 3, 2024
Clinical phenotypes among patients with normal cardiac perfusion using unsupervised learning: a retrospective observational study
Robert J H Miller, Bryan P Bednarski, Konrad Pieszko, et al.
Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology
|
April 12, 2018
Correction to: Clinical Quantification of Myocardial Blood Flow Using PET: Joint Position Paper of the SNMMI Cardiovascular Council and the ASNC
Venkatesh L Murthy, Timothy M Bateman, Rob S Beanlands, et al.
Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine
|
December 16, 2017
Clinical Quantification of Myocardial Blood Flow Using PET: Joint Position Paper of the SNMMI Cardiovascular Council and the ASNC
Venkatesh L Murthy, Timothy M Bateman, Rob S Beanlands, et al.
Page
of 22