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Institution · Heart Imaging Technologies (United States)

Most cited papers from Heart Imaging Technologies (United States)

Heart Imaging Technologies (United States)

What are the most cited papers from Heart Imaging Technologies (United States)?

The most cited paper from Heart Imaging Technologies (United States) is "Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer" (Babak Ehteshami Bejnordi et al., 2017), with 3,405 citations. Next come "Diagnostic accuracy of rest/stress ECG-gated Rb-82 myocardial perfusion PET: Comparison with ECG-gated Tc-99m sestamibi SPECT" (529) and "Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT" (358).

Showing 50 of 57 papers. Every paper with more than 19 citations is listed.

Most cited papers, sortable by citations and release date
#Paper
1 Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer Babak Ehteshami Bejnordi et al. · JAMA Open access 12 Dec 2017 3,405
2 Diagnostic accuracy of rest/stress ECG-gated Rb-82 myocardial perfusion PET: Comparison with ECG-gated Tc-99m sestamibi SPECT Timothy M. Bateman, Gary V. Heller, A. Iain McGhie et al. · Journal of Nuclear Cardiology 2006 529
3 Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT Julián Betancur, Frédéric Commandeur, M Esmaeili Motlagh et al. · JACC. Cardiovascular imaging Open access 18 Mar 2018 358
4 Spatially resolved measurements of hyperpolarized gas properties in the lung in vivo. Part I: Diffusion coefficient X. Josette Chen, Harald E. M�ller, Mark S. Chawla et al. · Magnetic Resonance in Medicine Open access Oct 1999 180
5 Myocardial blood flow reserve assessed by positron emission tomography myocardial perfusion imaging identifies patients with a survival benefit from early revascularization Krishna Patel, John A. Spertus, Paul S. Chan et al. · European Heart Journal Open access 20 May 2019 178
6 Quantification of Myocardial Blood Flow in Absolute Terms Using 82Rb PET Imaging Sergey V. Nesterov et al. · JACC. Cardiovascular imaging Open access 9 Oct 2014 170
7 Deep Learning Analysis of Upright-Supine High-Efficiency SPECT Myocardial Perfusion Imaging for Prediction of Obstructive Coronary Artery Disease: A Multicenter Study Julián Betancur, Lien-Hsin Hu, Frédéric Commandeur et al. · Journal of Nuclear Medicine Open access 27 Sep 2018 154
8 Prognostic Value of Vasodilator Stress Cardiac Magnetic Resonance Imaging John F. Heitner, Raymond J. Kim, Han W. Kim et al. · JAMA Cardiology Open access 8 Feb 2019 146
9 Independent and incremental prognostic value of left ventricular ejection fraction determined by stress gated rubidium 82 PET imaging in patients with known or suspected coronary artery disease Kirkeith Lertsburapa, Alan W. Ahlberg, Timothy M. Bateman et al. · Journal of Nuclear Cardiology 18 Sep 2008 136
10 Clinical Deployment of Explainable Artificial Intelligence of SPECT for Diagnosis of Coronary Artery Disease Yuka Otaki et al. · JACC. Cardiovascular imaging Open access 14 Jul 2021 122
11 Rationale and design of the REgistry of Fast Myocardial Perfusion Imaging with NExt generation SPECT (REFINE SPECT) Piotr J. Slomka et al. · Journal of Nuclear Cardiology Open access 19 Jun 2018 116
12 Issues regarding radiation dosage of cardiac nuclear and radiography procedures Randall C. Thompson, S. James Cullom · Journal of Nuclear Cardiology 2006 116
13 Extent of Myocardial Ischemia on Positron Emission Tomography and Survival Benefit With Early Revascularization Krishna Patel, John A. Spertus, Paul S. Chan et al. · Journal of the American College of Cardiology Open access 23 Sep 2019 106
14 Spatially resolved measurements of hyperpolarized gas properties in the lung in vivo. Part II:T?2 X. Josette Chen, Harald E. M�ller, Mark S. Chawla et al. · Magnetic Resonance in Medicine Oct 1999 103
15 Machine learning predicts per-vessel early coronary revascularization after fast myocardial perfusion SPECT: results from multicentre REFINE SPECT registry Lien-Hsin Hu et al. · European Heart Journal - Cardiovascular Imaging Open access 9 Jul 2019 101
16 Attenuation correction single-photon emission computed tomography myocardial perfusion imaging Timothy M. Bateman, S. James Cullom · Seminars in Nuclear Medicine 2005 100
17 A multicenter evaluation of a new post-processing method with depth-dependent collimator resolution applied to full-time and half-time acquisitions without and with simultaneously acquired attenuation correction Carmelo V. Venero, Gary V. Heller, Timothy M. Bateman et al. · Journal of Nuclear Cardiology 6 Jul 2009 100
18 5-Year Prognostic Value of Quantitative Versus Visual MPI in Subtle Perfusion Defects Yuka Otaki et al. · JACC. Cardiovascular imaging Open access 12 Jun 2019 96
19 Deep Learning of Coronary Calcium Scores From PET/CT Attenuation Maps Accurately Predicts Adverse Cardiovascular Events Konrad Pieszko, Aakash Dhananjay Shanbhag, Aditya Killekar et al. · JACC. Cardiovascular imaging Open access 14 Sep 2022 79
20 Attenuation artifact, attenuation correction, and the future of myocardial perfusion SPECT Bhupinder Singh, Timothy M. Bateman, James A. Case et al. · Journal of Nuclear Cardiology Open access 25 Mar 2007 79
21 Multicenter investigation comparing a highly efficient half-time stress-only attenuation correction approach against standard rest-stress Tc-99m SPECT imaging Timothy M. Bateman, Gary V. Heller, A. Iain McGhie et al. · Journal of Nuclear Cardiology 22 Jun 2009 78
22 Deep Learning Coronary Artery Calcium Scores from SPECT/CT Attenuation Maps Improve Prediction of Major Adverse Cardiac Events Robert J.H. Miller, Konrad Pieszko, Aakash Dhananjay Shanbhag et al. · Journal of Nuclear Medicine Open access 7 Oct 2022 67
23 Signal Dynamics in Magnetic Resonance Imaging of the Lung with Hyperpolarized Noble Gases Harald E. Möller, X. Josette Chen, Mark S. Chawla et al. · Journal of Magnetic Resonance Nov 1998 66
24 Diagnostic and clinical benefit of combined coronary calcium and perfusion assessment in patients undergoing PET/CT myocardial perfusion stress imaging Kevin A. Bybee, John Lee, Richard Markiewicz et al. · Journal of Nuclear Cardiology 10 Dec 2009 65
25 Prognostically safe stress-only single-photon emission computed tomography myocardial perfusion imaging guided by machine learning: report from REFINE SPECT Lien-Hsin Hu, Robert J.H. Miller, Tali Sharir et al. · European Heart Journal - Cardiovascular Imaging Open access 8 May 2020 64
26 Association of Total Cholesterol/High‐Density Lipoprotein Cholesterol Ratio With Proximal Coronary Atherosclerosis Detected by Multislice Computed Tomography Deepu V Nair, Thomas Carrigan, Ronan J. Curtin et al. · Preventive Cardiology Open access 2009 62
27 Practical Guide for Interpreting and Reporting Cardiac PET Measurements of Myocardial Blood Flow: An Information Statement from the American Society of Nuclear Cardiology, and the Society of Nuclear Medicine and Molecular Imaging Timothy M. Bateman, Gary V. Heller, Rob S. Beanlands et al. · Journal of Nuclear Medicine Open access 31 Mar 2021 61
28 Impact of Early Revascularization on Major Adverse Cardiovascular Events in Relation to Automatically Quantified Ischemia Peyman Nejatbakhsh Azadani et al. · JACC. Cardiovascular imaging Open access 19 Aug 2020 56
29 Magnetic resonance angiography with hyperpolarized129Xe dissolved in a lipid emulsion Harald E. M�ller, Mark S. Chawla, X. Josette Chen et al. · Magnetic Resonance in Medicine May 1999 52
30 Direct Risk Assessment From Myocardial Perfusion Imaging Using Explainable Deep Learning Ananya Singh et al. · JACC. Cardiovascular imaging Open access 19 Oct 2022 51
31 Contemporary Cardiac SPECT Imaging—Innovations and Best Practices: An Information Statement from the American Society of Nuclear Cardiology Brian Abbott, James A. Case, Sharmila Dorbala et al. · Journal of Nuclear Cardiology Open access 24 Aug 2018 48
32 Randomized Comparison of Clinical Effectiveness of Pharmacologic SPECT and PET MPI in Symptomatic CAD Patients Krishna Patel, Firas J. Al Badarin, Paul S. Chan et al. · JACC. Cardiovascular imaging Open access 17 Jul 2019 46
33 Handling missing values in machine learning to predict patient-specific risk of adverse cardiac events: Insights from REFINE SPECT registry Richard Ríos, Robert J.H. Miller, Nipun Manral et al. · Computers in Biology and Medicine Open access 25 Mar 2022 43
34 Determining a minimum set of variables for machine learning cardiovascular event prediction: results from REFINE SPECT registry Richard Ríos et al. · Cardiovascular Research Open access 7 Jul 2021 41
35 Sensitivity and resolution in 3D NMR microscopy of the lung with hyperpolarized noble gases Harald E. M�ller, X. Josette Chen, Mark S. Chawla et al. · Magnetic Resonance in Medicine Apr 1999 39
36 Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images Robert J.H. Miller et al. · European Journal of Nuclear Medicine and Molecular Imaging Open access 4 Oct 2022 38
37 Diagnostic safety of a machine learning-based automatic patient selection algorithm for stress-only myocardial perfusion SPECT Evann Eisenberg et al. · Journal of Nuclear Cardiology Open access 6 Jul 2021 38
38 Transient ischaemic dilation and post-stress wall motion abnormality increase risk in patients with less than moderate ischaemia: analysis of the REFINE SPECT registry Robert J.H. Miller et al. · European Heart Journal - Cardiovascular Imaging Open access 26 Jun 2019 38
39 Comparison Study of Capillary Pressure Curves Obtained Using Traditional Centrifuge and Magnetic Resonance Imaging Techniques Derrick Green, John F. Gardner, B. J. Balcom et al. Conference paper 20 Apr 2008 38
40 Taking the perfect nuclear image: Quality control, acquisition, and processing techniques for cardiac SPECT, PET, and hybrid imaging James A. Case, Timothy M. Bateman · Journal of Nuclear Cardiology 18 Jul 2013 38
41 Myocardial Ischemic Burden and Differences in Prognosis Among Patients With and Without Diabetes: Results From the Multicenter International REFINE SPECT Registry Donghee Han, Alan Rozanski, Heidi Gransar et al. · Diabetes Care Open access 27 Nov 2019 36
42 AI-Defined Cardiac Anatomy Improves Risk Stratification of Hybrid Perfusion Imaging Robert J.H. Miller, Aakash Dhananjay Shanbhag, Aditya Killekar et al. · JACC. Cardiovascular imaging Open access 6 Mar 2024 35
43 Explainable Deep Learning Improves Physician Interpretation of Myocardial Perfusion Imaging Robert J.H. Miller et al. · Journal of Nuclear Medicine Open access 5 May 2022 33
44 Status of cardiovascular PET radiation exposure and strategies for reduction: An Information Statement from the Cardiovascular PET Task Force James A. Case, Robert A. deKemp, Piotr J. Slomka et al. · Journal of Nuclear Cardiology Open access 16 May 2017 33
45 A Low-Power 0.7 $\mu {\rm V_{rms}}$ 32-Channel Mixed-Signal Circuit for ECoG Recordings S. Robinet, P. Audebert, Guillaume Regis et al. · IEEE Journal on Emerging and Selected Topics in Circuits and Systems Dec 2011 30
46 Time and event-specific deep learning for personalized risk assessment after cardiac perfusion imaging Konrad Pieszko et al. · npj Digital Medicine Open access May 2023 29
47 Automated vessel-specific coronary artery calcification quantification with deep learning in a large multi-centre registry Michelle Claire Williams, Aakash Dhananjay Shanbhag, Jianhang Zhou et al. · European Heart Journal - Cardiovascular Imaging Open access 20 Feb 2024 27
48 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 et al. · Journal of Nuclear Cardiology Open access 14 May 2019 26
49 The Updated Registry of Fast Myocardial Perfusion Imaging with Next-Generation SPECT (REFINE SPECT 2.0) Robert J.H. Miller et al. · Journal of Nuclear Medicine Open access 3 Oct 2024 23
50 Prognostic Value of Phase Analysis for Predicting Adverse Cardiac Events Beyond Conventional Single-Photon Emission Computed Tomography Variables: Results From the REFINE SPECT Registry Keiichiro Kuronuma et al. · Circulation Cardiovascular Imaging Open access Jul 2021 23

Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for an institution when any of its authors gave it as an affiliation; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.