Frédéric Commandeur

2.7k total citations
33 papers, 1.7k citations indexed

About

Frédéric Commandeur is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Biomedical Engineering. According to data from OpenAlex, Frédéric Commandeur has authored 33 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Radiology, Nuclear Medicine and Imaging, 14 papers in Cardiology and Cardiovascular Medicine and 10 papers in Biomedical Engineering. Recurrent topics in Frédéric Commandeur's work include Cardiac Imaging and Diagnostics (15 papers), Cardiovascular Disease and Adiposity (14 papers) and Advanced X-ray and CT Imaging (6 papers). Frédéric Commandeur is often cited by papers focused on Cardiac Imaging and Diagnostics (15 papers), Cardiovascular Disease and Adiposity (14 papers) and Advanced X-ray and CT Imaging (6 papers). Frédéric Commandeur collaborates with scholars based in United States, Germany and France. Frédéric Commandeur's co-authors include Damini Dey, Piotr J. Slomka, Daniel S. Berman, Balaji Tamarappoo, Markus Goeller, Sebastien Cadet, Xi Chen, Stephan Achenbach, Heidi Gransar and Mohamed Marwan and has published in prestigious journals such as Circulation, Journal of the American College of Cardiology and European Heart Journal.

In The Last Decade

Frédéric Commandeur

33 papers receiving 1.7k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Frédéric Commandeur United States	17	1.1k	1.0k	489	388	190	33	1.7k
Yuka Otaki United States	25	1.5k 1.5×	1.0k 1.0×	746 1.5×	629 1.6×	226 1.2×	89	2.2k
Markus Goeller Germany	18	881 0.8×	1.1k 1.1×	609 1.2×	276 0.7×	122 0.6×	36	1.5k
Sebastien Cadet United States	27	1.5k 1.4×	1.4k 1.3×	811 1.7×	387 1.0×	345 1.8×	60	2.3k
Reza Arsanjani United States	23	1.1k 1.1×	1.1k 1.1×	548 1.1×	408 1.1×	228 1.2×	175	2.1k
Marly van Assen United States	24	1.2k 1.1×	476 0.5×	344 0.7×	714 1.8×	153 0.8×	89	1.5k
Tali Sharir United States	24	2.2k 2.1×	1.1k 1.0×	402 0.8×	884 2.3×	59 0.3×	50	2.6k
Alaa Mabrouk Salem Omar United States	11	610 0.6×	844 0.8×	176 0.4×	116 0.3×	91 0.5×	55	1.2k
Christopher M. Haggerty United States	30	403 0.4×	1.2k 1.1×	510 1.0×	257 0.7×	413 2.2×	103	2.0k
Jeremy R. Burt United States	15	532 0.5×	352 0.3×	143 0.3×	169 0.4×	216 1.1×	69	952
Nikolas Leßmann Netherlands	17	725 0.7×	202 0.2×	256 0.5×	614 1.6×	169 0.9×	34	1.2k

Countries citing papers authored by Frédéric Commandeur

Since Specialization

Citations

This map shows the geographic impact of Frédéric Commandeur'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 Frédéric Commandeur with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frédéric Commandeur more than expected).

Fields of papers citing papers by Frédéric Commandeur

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Frédéric Commandeur. 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 Frédéric Commandeur. The network helps show where Frédéric Commandeur may publish in the future.

Co-authorship network of co-authors of Frédéric Commandeur

This figure shows the co-authorship network connecting the top 25 collaborators of Frédéric Commandeur. A scholar is included among the top collaborators of Frédéric Commandeur 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 Frédéric Commandeur. Frédéric Commandeur is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Lin, Andrew, Nathan D. Wong, Aryabod Razipour, et al.. (2021). Metabolic syndrome, fatty liver, and artificial intelligence-based epicardial adipose tissue measures predict long-term risk of cardiac events: a prospective study. Cardiovascular Diabetology. 20(1). 27–27. 40 indexed citations

Hu, Lien-Hsin, Robert J.H. Miller, Tali Sharir, et al.. (2020). Prognostically safe stress-only single-photon emission computed tomography myocardial perfusion imaging guided by machine learning: report from REFINE SPECT. European Heart Journal - Cardiovascular Imaging. 22(6). 705–714. 36 indexed citations

Commandeur, Frédéric, Markus Goeller, Aryabod Razipour, et al.. (2019). Fully Automated CT Quantification of Epicardial Adipose Tissue by Deep Learning: A Multicenter Study. Radiology Artificial Intelligence. 1(6). e190045–e190045. 94 indexed citations

Hong, Youngtaek, Frédéric Commandeur, Sebastien Cadet, et al.. (2019). Deep learning-based stenosis quantification from coronary CT angiography. PubMed. 10949. 88–88. 42 indexed citations

Commandeur, Frédéric, Piotr J. Slomka, Markus Goeller, et al.. (2019). 30Machine learning to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium and epicardial adipose tissue: a prospective study. European Heart Journal. 40(Supplement_1). 15 indexed citations

Commandeur, Frédéric, Piotr J. Slomka, Markus Goeller, et al.. (2019). Machine learning to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium, and epicardial adipose tissue: a prospective study. Cardiovascular Research. 116(14). 2216–2225. 102 indexed citations

Goeller, Markus, Balaji Tamarappoo, Alan C. Kwan, et al.. (2018). Abstract 15929: Relationship Between Changes in Pericoronary Adipose Tissue Attenuation and Plaque Progression by Coronary CTA. Circulation. 1 indexed citations

Betancur, Julián, Frédéric Commandeur, Tali Sharir, et al.. (2018). Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT. JACC. Cardiovascular imaging. 11(11). 1654–1663. 224 indexed citations

Betancur, Julián, Lien-Hsin Hu, Frédéric Commandeur, et al.. (2018). Deep Learning Analysis of Upright-Supine High-Efficiency SPECT Myocardial Perfusion Imaging for Prediction of Obstructive Coronary Artery Disease: A Multicenter Study. Journal of Nuclear Medicine. 60(5). 664–670. 95 indexed citations

10.

Commandeur, Frédéric, Markus Goeller, & Damini Dey. (2018). Cardiac CT: Technological Advances in Hardware, Software, and Machine Learning Applications. Current Cardiovascular Imaging Reports. 11(8). 12 indexed citations

11.

Commandeur, Frédéric, Markus Goeller, Julián Betancur, et al.. (2018). Deep Learning for Quantification of Epicardial and Thoracic Adipose Tissue From Non-Contrast CT. IEEE Transactions on Medical Imaging. 37(8). 1835–1846. 134 indexed citations

12.

Nakanishi, Rine, Damini Dey, Frédéric Commandeur, et al.. (2018). MACHINE LEARNING IN PREDICTING CORONARY HEART DISEASE AND CARDIOVASCULAR DISEASE EVENTS: RESULTS FROM THE MULTI-ETHNIC STUDY OF ATHEROSCLEROSIS (MESA). Journal of the American College of Cardiology. 71(11). A1483–A1483. 19 indexed citations

13.

Goeller, Markus, Stephan Achenbach, Mohamed Marwan, et al.. (2017). Epicardial adipose tissue density and volume are related to subclinical atherosclerosis, inflammation and major adverse cardiac events in asymptomatic subjects. Journal of cardiovascular computed tomography. 12(1). 67–73. 166 indexed citations

14.

Crevoisier, R. de, Juan David Ospina, Frédéric Commandeur, et al.. (2017). Population model of bladder motion and deformation based on dominant eigenmodes and mixed-effects models in prostate cancer radiotherapy. Medical Image Analysis. 38. 133–149. 17 indexed citations

15.

Guzman, Lina, Frédéric Commandeur, Oscar Acosta, et al.. (2016). Slice correspondence estimation using SURF descriptors and context-based search for prostate whole-mount histology MRI registration. PubMed. 3951. 1163–1166. 4 indexed citations

16.

Commandeur, Frédéric, Oscar Acosta, Antoine Simon, et al.. (2015). Prostate whole-mount histology reconstruction and registration to MRI for correlating in-vivo observations with biological findings. PubMed. 2015. 2399–2402. 9 indexed citations

17.

Commandeur, Frédéric, Oscar Acosta, Antoine Simon, et al.. (2015). Segmentation of prostate from CT scans using a combined voxel random forests classification with spherical harmonics regularization. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9287. 92870F–92870F. 1 indexed citations

18.

Khalifa, Jonathan, Frédéric Commandeur, Jean‐Marc Bachaud, & R. de Crevoisier. (2013). Radiothérapie conformationnelle prostatique : quelles marges ?. Cancer/Radiothérapie. 17(5-6). 461–469. 9 indexed citations

19.

Ospina, Juan David, Frédéric Commandeur, Juan Carlos Correa, et al.. (2013). A Tensor-Based Population Value Decomposition to Explain Rectal Toxicity after Prostate Cancer Radiotherapy. Lecture notes in computer science. 16(Pt 2). 387–394. 4 indexed citations

20.

Commandeur, Frédéric, et al.. (2011). A VTK Algorithm for the Computation of the Hausdorff Distance. 11 indexed citations

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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