James Otton

1.6k total citations
54 papers, 895 citations indexed

About

James Otton is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. According to data from OpenAlex, James Otton has authored 54 papers receiving a total of 895 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Cardiology and Cardiovascular Medicine, 32 papers in Radiology, Nuclear Medicine and Imaging and 17 papers in Biomedical Engineering. Recurrent topics in James Otton's work include Cardiac Imaging and Diagnostics (28 papers), Cardiovascular Function and Risk Factors (15 papers) and Advanced X-ray and CT Imaging (10 papers). James Otton is often cited by papers focused on Cardiac Imaging and Diagnostics (28 papers), Cardiovascular Function and Risk Factors (15 papers) and Advanced X-ray and CT Imaging (10 papers). James Otton collaborates with scholars based in Australia, United Kingdom and Germany. James Otton's co-authors include Nalini Pather, Eike Nagel, Chung-Yao Yu, Sven Plein, Valentina O. Püntmann, Andrew Jabbour, Nicholas Child, Bernhard Schnackenburg, Darius Dabir and Ananth Kidambi and has published in prestigious journals such as Journal of the American College of Cardiology, PLoS ONE and Scientific Reports.

In The Last Decade

James Otton

50 papers receiving 882 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
James Otton Australia 16 480 459 217 212 108 54 895
Andrew J. Ford United States 12 242 0.5× 208 0.5× 101 0.5× 266 1.3× 44 0.4× 14 555
Elena Giulia Milano United Kingdom 11 221 0.5× 171 0.4× 99 0.5× 194 0.9× 228 2.1× 26 545
René Nkoulou Switzerland 24 356 0.7× 1.4k 3.1× 676 3.1× 271 1.3× 141 1.3× 60 1.7k
Touko Kaasalainen Finland 15 153 0.3× 512 1.1× 324 1.5× 65 0.3× 91 0.8× 48 789
Kenneth J. Resser United States 14 432 0.9× 534 1.2× 128 0.6× 223 1.1× 126 1.2× 18 906
Kentaro Takanami Japan 15 215 0.4× 345 0.8× 69 0.3× 295 1.4× 241 2.2× 60 778
Ullrich Ebersberger Germany 24 564 1.2× 1.2k 2.6× 735 3.4× 358 1.7× 149 1.4× 72 1.6k
Thomas Henzler Germany 16 105 0.2× 523 1.1× 327 1.5× 141 0.7× 78 0.7× 36 798
Priyanka Prakash United States 13 48 0.1× 684 1.5× 564 2.6× 124 0.6× 136 1.3× 20 982
Annemarie M. den Harder Netherlands 17 85 0.2× 496 1.1× 335 1.5× 141 0.7× 223 2.1× 40 868

Countries citing papers authored by James Otton

Since Specialization
Citations

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

Fields of papers citing papers by James Otton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James Otton

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

All Works

20 of 20 papers shown
1.
Chlap, Phillip, Lois Holloway, David Thwaites, et al.. (2024). Dosimetric Impact of Delineation and Motion Uncertainties on the Heart and Substructures in Lung Cancer Radiotherapy. Clinical Oncology. 36(7). 420–429. 1 indexed citations
2.
Chlap, Phillip, Eric Hau, Xinliang Ma, et al.. (2024). Cardiac Substructure Dose and Survival in Stereotactic Radiotherapy for Lung Cancer: Results of the Multi-Centre SSBROC Trial. Clinical Oncology. 36(10). 642–650. 1 indexed citations
3.
Keall, Paul, et al.. (2024). Overview of cardiac toxicity from radiation therapy. Journal of Medical Imaging and Radiation Oncology. 68(8). 987–1000. 1 indexed citations
4.
5.
Playford, David, et al.. (2023). Prognostic association supports indexing size measures in echocardiography by body surface area. Scientific Reports. 13(1). 19390–19390. 6 indexed citations
6.
Playford, David, et al.. (2023). Decreased diastolic hydraulic forces incrementally associate with survival beyond conventional measures of diastolic dysfunction. Scientific Reports. 13(1). 16396–16396. 5 indexed citations
7.
Abed, Amr Al, Azam Ahmad Bakir, Nigel H. Lovell, et al.. (2022). Fluid structure computational model of simulating mitral valve motion in a contracting left ventricle. Computers in Biology and Medicine. 148. 105834–105834. 9 indexed citations
8.
Gharleghi, Ramtin, Claire A. Dessalles, Nigel Jepson, et al.. (2021). 3D Printing for Cardiovascular Applications: From End-to-End Processes to Emerging Developments. Annals of Biomedical Engineering. 49(7). 1598–1618. 26 indexed citations
9.
Giau, Vo Van, et al.. (2021). Direct comparison of multilayer left ventricular global longitudinal strain using CMR feature tracking and speckle tracking echocardiography. BMC Cardiovascular Disorders. 21(1). 107–107. 11 indexed citations
10.
Imran, Muhammad, Jane McCrohon, Cameron J. Holloway, et al.. (2019). Native T1 Mapping in the Diagnosis of Cardiac Allograft Rejection. JACC. Cardiovascular imaging. 12(8). 1618–1628. 33 indexed citations
11.
Otton, James, et al.. (2019). Predicting the outcome of transcatheter mitral valve implantation using image-based computational models. Journal of cardiovascular computed tomography. 14(4). 335–342. 19 indexed citations
12.
Otton, James & David W.M. Muller. (2017). Apically Tethered Transcatheter Mitral Valve Implantation. JACC: Cardiovascular Interventions. 10(6). e61–e63. 2 indexed citations
13.
Otton, James, et al.. (2017). 3D printing from cardiovascular CT: a practical guide and review. Cardiovascular Diagnosis and Therapy. 7(5). 507–526. 56 indexed citations
14.
Otton, James, et al.. (2017). 3D Modelling and Printing Technology to Produce Patient-Specific 3D Models. Heart Lung and Circulation. 28(2). 302–313. 39 indexed citations
15.
Nguyen, T., Leia Hee, Daniel Moses, et al.. (2016). Adverse diastolic remodeling after reperfused ST-elevation myocardial infarction: An important prognostic indicator. American Heart Journal. 180. 117–127. 11 indexed citations
16.
Nguyen, T., Leia Hee, James Otton, et al.. (2016). Electrocardiographic measurement of infarct size compared to cardiac MRI in reperfused first time ST-segment elevation myocardial infarction. International Journal of Cardiology. 220. 389–394. 7 indexed citations
17.
18.
Otton, James, Chung-Yao Yu, Jane McCrohon, Neville Sammel, & Michael P. Feneley. (2013). ACCURACY AND CLINICAL OUTCOMES OF COMPUTED TOMOGRAPHY CORONARY ANGIOGRAPHY IN THE PRESENCE OF A HIGH CORONARY CALCIUM SCORE. Journal of the American College of Cardiology. 61(10). E912–E912. 1 indexed citations
19.
Otton, James, Chung-Yao Yu, Jane McCrohon, Neville Sammel, & Michael P. Feneley. (2013). Accuracy and Clinical Outcomes of Computed Tomography Coronary Angiography in the Presence of a High Coronary Calcium Score. Heart Lung and Circulation. 22(12). 980–986. 9 indexed citations
20.
Chiribiri, Amedeo, Andreas Schuster, Masaki Ishida, et al.. (2012). Perfusion phantom: An efficient and reproducible method to simulate myocardial first‐pass perfusion measurements with cardiovascular magnetic resonance. Magnetic Resonance in Medicine. 69(3). 698–707. 37 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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