El-Sayed H. Ibrahim

475 total citations
25 papers, 301 citations indexed

About

El-Sayed H. Ibrahim is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Biomedical Engineering. According to data from OpenAlex, El-Sayed H. Ibrahim has authored 25 papers receiving a total of 301 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Radiology, Nuclear Medicine and Imaging, 17 papers in Cardiology and Cardiovascular Medicine and 4 papers in Biomedical Engineering. Recurrent topics in El-Sayed H. Ibrahim's work include Advanced MRI Techniques and Applications (17 papers), Cardiac Imaging and Diagnostics (16 papers) and Cardiovascular Function and Risk Factors (7 papers). El-Sayed H. Ibrahim is often cited by papers focused on Advanced MRI Techniques and Applications (17 papers), Cardiac Imaging and Diagnostics (16 papers) and Cardiovascular Function and Risk Factors (7 papers). El-Sayed H. Ibrahim collaborates with scholars based in United States, Egypt and Germany. El-Sayed H. Ibrahim's co-authors include Jadranka Stojanovska, Grigorios Korosoglou, Amr Youssef, Elizabeth Lee, Shenghan Lai, Nael F. Osman, Kenneth C. Bilchick, Anil Attili, Albert C. Lardo and Jeremy D. Collins and has published in prestigious journals such as Scientific Reports, American Journal of Roentgenology and Radiographics.

In The Last Decade

El-Sayed H. Ibrahim

23 papers receiving 298 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
El-Sayed H. Ibrahim United States 10 208 194 42 33 28 25 301
Lau Brix Denmark 6 115 0.6× 183 0.9× 61 1.5× 42 1.3× 56 2.0× 26 286
Felicia Seemann Sweden 10 222 1.1× 112 0.6× 50 1.2× 26 0.8× 35 1.3× 22 259
Daniel A. Auger United States 13 309 1.5× 257 1.3× 50 1.2× 35 1.1× 50 1.8× 20 384
Archontis Giannakidis United Kingdom 8 185 0.9× 191 1.0× 60 1.4× 44 1.3× 24 0.9× 24 353
Hein W. M. Kayser Netherlands 10 367 1.8× 296 1.5× 48 1.1× 28 0.8× 41 1.5× 14 517
Stefan P. Karwatowski United Kingdom 10 242 1.2× 291 1.5× 38 0.9× 37 1.1× 24 0.9× 14 376
Tarinee Tangcharoen Thailand 9 160 0.8× 178 0.9× 65 1.5× 29 0.9× 82 2.9× 24 306
Pei G. Chew United Kingdom 12 353 1.7× 285 1.5× 67 1.6× 22 0.7× 29 1.0× 27 444
Jonathan M Hasleton United Kingdom 3 388 1.9× 328 1.7× 93 2.2× 30 0.9× 16 0.6× 5 506
Sabrina Oebel Germany 8 215 1.0× 259 1.3× 39 0.9× 87 2.6× 23 0.8× 24 369

Countries citing papers authored by El-Sayed H. Ibrahim

Since Specialization
Citations

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

Fields of papers citing papers by El-Sayed H. Ibrahim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by El-Sayed H. Ibrahim. 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 El-Sayed H. Ibrahim. The network helps show where El-Sayed H. Ibrahim may publish in the future.

Co-authorship network of co-authors of El-Sayed H. Ibrahim

This figure shows the co-authorship network connecting the top 25 collaborators of El-Sayed H. Ibrahim. A scholar is included among the top collaborators of El-Sayed H. Ibrahim 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 El-Sayed H. Ibrahim. El-Sayed H. Ibrahim 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.
Ibrahim, El-Sayed H., et al.. (2025). Cardiac MRI for differentiating chemotherapy-induced cardiotoxicity in sarcoma and breast cancer. Radiology and Oncology. 59(1). 79–90.
2.
3.
Woods, Ronald K., et al.. (2022). Clinical, Experimental, and Computational Validation of a New Doppler-Based Index for Coarctation Severity Assessment. Journal of the American Society of Echocardiography. 35(12). 1311–1321. 4 indexed citations
4.
Rajiah, Prabhakar, Kevin Kalisz, Jordi Broncano, et al.. (2022). Myocardial Strain Evaluation with Cardiovascular MRI: Physics, Principles, and Clinical Applications. Radiographics. 42(4). 968–990. 54 indexed citations
5.
Lee, Elizabeth, El-Sayed H. Ibrahim, Nancy Dudek, et al.. (2021). Improving MR Image Quality in Patients with Metallic Implants. Radiographics. 41(4). E126–E137. 35 indexed citations
6.
Bergom, Carmen, Jason Rubenstein, J. Frank Wilson, et al.. (2020). A Pilot Study of Cardiac MRI in Breast Cancer Survivors After Cardiotoxic Chemotherapy and Three-Dimensional Conformal Radiotherapy. Frontiers in Oncology. 10. 506739–506739. 12 indexed citations
7.
Lee, Elizabeth, El-Sayed H. Ibrahim, Purvi Parwani, Nicole M. Bhave, & Jadranka Stojanovska. (2020). Practical Guide to Evaluating Myocardial Disease by Cardiac MRI. American Journal of Roentgenology. 214(3). 546–556. 23 indexed citations
8.
Hamad, Rabab S., et al.. (2020). Graphene nanoparticles-based ELISA as a crucial new diagnostic tool for diagnosis of human filariasis. International Journal of Infectious Diseases. 101. 420–420. 1 indexed citations
9.
Ibrahim, El-Sayed H., et al.. (2020). Cardiac functional magnetic resonance imaging at 7T: Image quality optimization and ultra-high field capabilities. World Journal of Radiology. 12(10). 231–246. 7 indexed citations
10.
11.
Stojanovska, Jadranka, et al.. (2019). Left Ventricular Hypertrophy: Evaluation With Cardiac MRI. Current Problems in Diagnostic Radiology. 49(6). 460–475. 22 indexed citations
12.
Ibrahim, El-Sayed H., Jadranka Stojanovska, Claire S. Duvernoy, et al.. (2018). Regional cardiac function analysis from tagged MRI images. Comparison of techniques: Harmonic-Phase (HARP) versus Sinusoidal-Modeling (SinMod) analysis. Magnetic Resonance Imaging. 54. 271–282. 8 indexed citations
13.
14.
Ibrahim, El-Sayed H.. (2017). Heart Mechanics : Magnetic Resonance Imaging—Mathematical Modeling, Pulse Sequences, and Image Analysis. CRC Press eBooks. 2 indexed citations
15.
Stojanovska, Jadranka, El-Sayed H. Ibrahim, Aamer Chughtai, et al.. (2017). Intrathoracic Fat Measurements Using Multidetector Computed Tomography (MDCT): Feasibility and Reproducibility. Tomography. 3(1). 33–40. 2 indexed citations
16.
Ibrahim, El-Sayed H., Steven Swanson, Jadranka Stojanovska, Claire S. Duvernoy, & Rodica Pop‐Busui. (2016). Harmonic phase versus sine-wave modulation for measuring regional heart function from tagged MRI images. 57. 444–447. 2 indexed citations
17.
Khalifa, Ayman M., et al.. (2016). The influence of the analysis technique on myocardial T1 estimation using MRI. 74. 102–105.
18.
El‐Rewaidy, Hossam, El-Sayed H. Ibrahim, & Ahmed S. Fahmy. (2016). Segmentation of the right ventricle in MRI images using a dual active shape model. IET Image Processing. 10(10). 717–723. 10 indexed citations
19.
Ibrahim, El-Sayed H., Wolfgang Rehwald, Bradley P. Sutton, Sven Zuehlsdorff, & Richard D. White. (2011). Assessment of myocardial strain using strain-encoding (SENC) MRI: comparison of acquisition strategies. Journal of Cardiovascular Magnetic Resonance. 13(S1). 2 indexed citations
20.
Korosoglou, Grigorios, Amr Youssef, Kenneth C. Bilchick, et al.. (2008). Real‐time fast strain‐encoded magnetic resonance imaging to evaluate regional myocardial function at 3.0 Tesla: Comparison to conventional tagging. Journal of Magnetic Resonance Imaging. 27(5). 1012–1018. 59 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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