Peter Kellman
About
Peter Kellman is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Atomic and Molecular Physics, and Optics.
According to data from OpenAlex, Peter Kellman has authored 373 papers receiving a total of 18.8k indexed citations (citations by other indexed papers that have themselves been cited), including 304 papers in Radiology, Nuclear Medicine and Imaging, 176 papers in Cardiology and Cardiovascular Medicine and 49 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Peter Kellman's work include Advanced MRI Techniques and Applications (247 papers), Cardiac Imaging and Diagnostics (244 papers) and Cardiovascular Function and Risk Factors (107 papers). Peter Kellman is often cited by papers focused on Advanced MRI Techniques and Applications (247 papers), Cardiac Imaging and Diagnostics (244 papers) and Cardiovascular Function and Risk Factors (107 papers). Peter Kellman collaborates with scholars based in United States, United Kingdom and Germany. Peter Kellman's co-authors include Andrew E. Arai, Elliot R. McVeigh, Michael S. Hansen, Anthony H. Aletras, Martin Ugander, James Moon, Hui Xue, Erik B. Schelbert, Diego Hernando and Li‐Yueh Hsu and has published in prestigious journals such as JAMA, Circulation and SHILAP Revista de lepidopterología.
In The Last Decade
Peter Kellman
353 papers receiving 18.6k citations
Hit Papers
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late) cites · hero ref
| Name | h | Career | Trend | Papers | Cites | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| Peter Kellman United States | 74 | 13.3k | 9.8k | 2.0k | 1.8k | 1.5k | 373 | 18.8k | ||
| Matthew D. Robson United Kingdom | 67 | 10.0k 0.7× | 7.8k 0.8× | 1.2k 0.6× | 1.9k 1.0× | 930 0.6× | 243 | 16.9k | ||
| Andrew E. Arai United States | 71 | 10.6k 0.8× | 9.1k 0.9× | 1.5k 0.8× | 2.3k 1.2× | 697 0.5× | 307 | 16.6k | ||
| Eike Nagel Germany | 68 | 14.3k 1.1× | 12.5k 1.3× | 786 0.4× | 3.8k 2.1× | 757 0.5× | 431 | 21.2k | ||
| Michael Jerosch‐Herold United States | 67 | 7.9k 0.6× | 8.8k 0.9× | 934 0.5× | 2.2k 1.2× | 390 0.3× | 297 | 14.2k | ||
| Sven Plein United Kingdom | 59 | 10.8k 0.8× | 10.1k 1.0× | 624 0.3× | 3.0k 1.6× | 597 0.4× | 497 | 16.3k | ||
| Jeanette Schulz‐Menger Germany | 55 | 8.4k 0.6× | 11.8k 1.2× | 831 0.4× | 2.4k 1.3× | 507 0.3× | 286 | 16.0k | ||
| Stefan K. Piechnik United Kingdom | 56 | 6.6k 0.5× | 6.5k 0.7× | 1.3k 0.7× | 1.3k 0.7× | 236 0.2× | 217 | 12.4k | ||
| Eckart Fleck Germany | 59 | 5.7k 0.4× | 7.1k 0.7× | 3.0k 1.6× | 2.8k 1.5× | 386 0.3× | 413 | 14.4k | ||
| Dudley J. Pennell United Kingdom | 88 | 19.0k 1.4× | 23.8k 2.4× | 2.0k 1.0× | 6.1k 3.3× | 770 0.5× | 603 | 38.5k | ||
| Scott B. Reeder United States | 68 | 11.1k 0.8× | 2.9k 0.3× | 851 0.4× | 2.4k 1.3× | 1.0k 0.7× | 397 | 19.6k |
Countries citing papers authored by Peter Kellman
Since
Specialization
Citations
This map shows the geographic impact of Peter Kellman's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Peter Kellman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Kellman more than expected).
Fields of papers citing papers by Peter Kellman
Since
Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences
This network shows the impact of papers produced by Peter Kellman. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Peter Kellman. The network helps show where Peter Kellman may publish in the future.
Co-authorship network of co-authors of Peter Kellman
This figure shows the co-authorship network connecting the top 25 collaborators of Peter Kellman. A scholar is included among the top collaborators of Peter Kellman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Peter Kellman. Peter Kellman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
1.
Tomoaia, Raluca, Eylem Levelt, Lee Graham, et al.. (2025). Ventricular Arrhythmia and Cardiac Fibrosis in Endurance Experienced Athletes (VENTOUX). Circulation Cardiovascular Imaging. 18(8). e018470–e018470.
2.
Marvao, Antonio de, Mit Shah, Paolo Inglese, et al.. (2025). Establishing Cardiac MRI Reference Ranges Stratified by Sex and Age for Cardiovascular Function during Exercise. Radiology Cardiothoracic Imaging. 7(3). e240175–e240175.
3.
Tomoaia, Raluca, B.R. Chambers, Louise Brown, et al.. (2025). Cardiovascular magnetic resonance to differentiate veteran athlete’s heart with cavity dilatation and mild dilated cardiomyopathy. European Heart Journal - Cardiovascular Imaging. 26(11). 1762–1770.
4.
Giannoudi, Marilena, Amrit Chowdhary, Nicholas Jex, et al.. (2024). Cardiac structural, functional, and energetic assessments during and after pregnancy in women with gestational diabetes mellitus, preeclampsia, and healthy pregnancy. American Journal of Obstetrics and Gynecology. 232(6). 565.e1–565.e16.
5.
Patel, Rishi, Ana Martinez–Naharro, Yousuf Razvi, et al.. (2024). 5 Cardiovascular magnetic resonance (CMR) in transthyretin amyloid cardiomyopathy – a study of natural history and treatment repsonse. Abstracts. A2.1–A2.
6.
Netti, Lucrezia, Adam Ioannou, Ana Martinez–Naharro, et al.. (2024). Microvascular Obstruction in Cardiac Amyloidosis. European Journal of Heart Failure. 27(12). 2948–2951.
7.
Biglands, John, David Broadbent, Peter Kellman, et al.. (2023). The impact of water exchange on estimates of myocardial extracellular volume calculated using contrast enhanced T1 measurements: A preliminary analysis in patients with severe aortic stenosis. Magnetic Resonance in Medicine. 91(4). 1637–1644.
8.
Hughes, Rebecca, Hunain Shiwani, Stefania Rosmini, et al.. (2023). Improved Diagnostic Criteria for Apical Hypertrophic Cardiomyopathy. JACC. Cardiovascular imaging. 17(5). 501–512.
9.
Brown, Louise, Nicholas Jex, Amrit Chowdhary, et al.. (2023). 8 Adverse cardiovascular outcomes in diabetic patients with heart failure are mediated by silent myocardial infarction. Abstracts. A7.1–A7.
10.
Nickander, Jannike, Judith Bruchfeld, Michael Runold, et al.. (2023). Stress native T1 and native T2 mapping compared to myocardial perfusion reserve in long-term follow-up of severe Covid-19. Scientific Reports. 13(1). 4159–4159.
11.
Gulsin, Gaurav S., Emer M. Brady, Anna-Marie Marsh, et al.. (2021). Clinical associations with stage B heart failure in adults with type 2 diabetes. Therapeutic Advances in Endocrinology and Metabolism. 12. 2425399424–2425399424.
12.
Bhuva, Anish, Thomas A. Treibel, Andreas Seraphim, et al.. (2021). Measurement of T1 Mapping in Patients With Cardiac Devices: Off-Resonance Error Extends Beyond Visual Artifact but Can Be Quantified and Corrected. Frontiers in Cardiovascular Medicine. 8. 631366–631366.
13.
Kotecha, Tushar, Juan Manuel Monteagudo Ruiz, Ana Martinez–Naharro, et al.. (2020). Quantitative cardiovascular magnetic resonance myocardial perfusion mapping to assess hyperaemic response to adenosine stress. European Heart Journal - Cardiovascular Imaging. 22(3). 273–281.
14.
Xue, Hui, Rhodri Davies, Louise Brown, et al.. (2020). Automated Inline Analysis of Myocardial Perfusion MRI with Deep Learning. Radiology Artificial Intelligence. 2(6). e200009–e200009.
15.
Camaioni, Claudia, Kristopher Knott, João B. Augusto, et al.. (2019). Inline perfusion mapping provides insights into the disease mechanism in hypertrophic cardiomyopathy. Heart. 106(11). 824–829.
16.
Ramasawmy, Rajiv, Toby Rogers, Miguel A. Alcantar, et al.. (2018). Blood volume measurement using cardiovascular magnetic resonance and ferumoxytol: preclinical validation. Journal of Cardiovascular Magnetic Resonance. 20(1). 62–62.
17.
Martinez–Naharro, Ana, Amna Abdel‐Gadir, Thomas A. Treibel, et al.. (2016). Abstract 14407: Regression of Cardiac AL Amyloid by Cardiovascular Magnetic Resonance. Circulation. 134.
18.
Wong, Timothy C., Kayla Piehler, Christopher G Meier, et al.. (2012). Association Between Extracellular Matrix Expansion Quantified by Cardiovascular Magnetic Resonance and Short-Term Mortality. Circulation. 126(10). 1206–1216.
19.
Hernando, Diego, Zhi‐Pei Liang, & Peter Kellman. (2010). Chemical shift–based water/fat separation: A comparison of signal models. Magnetic Resonance in Medicine. 64(3). 811–822.
20.
Hsu, Li‐Yueh, et al.. (2006). Quantitative myocardial perfusion analysis with a dual‐bolus contrast‐enhanced first‐pass MRI technique in humans. Journal of Magnetic Resonance Imaging. 23(3). 315–322.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
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