Mohammed S.M. Elbaz

1.6k total citations
50 papers, 1.1k citations indexed

About

Mohammed S.M. Elbaz is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Epidemiology. According to data from OpenAlex, Mohammed S.M. Elbaz has authored 50 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Cardiology and Cardiovascular Medicine, 25 papers in Radiology, Nuclear Medicine and Imaging and 13 papers in Epidemiology. Recurrent topics in Mohammed S.M. Elbaz's work include Cardiovascular Function and Risk Factors (26 papers), Advanced MRI Techniques and Applications (20 papers) and Cardiac Valve Diseases and Treatments (19 papers). Mohammed S.M. Elbaz is often cited by papers focused on Cardiovascular Function and Risk Factors (26 papers), Advanced MRI Techniques and Applications (20 papers) and Cardiac Valve Diseases and Treatments (19 papers). Mohammed S.M. Elbaz collaborates with scholars based in United States, Netherlands and United Kingdom. Mohammed S.M. Elbaz's co-authors include Jos J.M. Westenberg, Rob J. van der Geest, Arno A.W. Roest, Emmeline E. Calkoen, Boudewijn P. F. Lelieveldt, Albert de Roos, Pankaj Garg, Michael Markl, Sven Plein and Vivian P. Kamphuis and has published in prestigious journals such as JNCI Journal of the National Cancer Institute, Stroke and Radiology.

In The Last Decade

Mohammed S.M. Elbaz

48 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mohammed S.M. Elbaz United States	19	803	509	258	238	146	50	1.1k
Miguel Ares Spain	13	1.3k 1.6×	754 1.5×	132 0.5×	161 0.7×	175 1.2×	30	1.6k
Freddy Odille France	20	456 0.6×	873 1.7×	139 0.5×	175 0.7×	279 1.9×	93	1.5k
Johannes Schwab Germany	17	725 0.9×	283 0.6×	133 0.5×	152 0.6×	276 1.9×	53	925
Alejandro Roldán‐Alzate United States	21	458 0.6×	356 0.7×	418 1.6×	409 1.7×	212 1.5×	74	1.1k
Eva Sammut United Kingdom	20	802 1.0×	495 1.0×	175 0.7×	85 0.4×	277 1.9×	67	1.2k
Raymond H. Chan United States	28	2.2k 2.7×	523 1.0×	111 0.4×	359 1.5×	279 1.9×	71	2.6k
Henry Chubb United Kingdom	21	1.0k 1.3×	347 0.7×	174 0.7×	267 1.1×	174 1.2×	86	1.4k
Peter Weale United Kingdom	17	610 0.8×	818 1.6×	279 1.1×	112 0.5×	196 1.3×	35	1.2k
Ryan Avery United States	12	224 0.3×	234 0.5×	236 0.9×	70 0.3×	115 0.8×	84	586
Maximilian Frederik Russe Germany	18	653 0.8×	668 1.3×	648 2.5×	218 0.9×	316 2.2×	75	1.5k

Countries citing papers authored by Mohammed S.M. Elbaz

Since Specialization

Citations

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

Fields of papers citing papers by Mohammed S.M. Elbaz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohammed S.M. Elbaz. 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 Mohammed S.M. Elbaz. The network helps show where Mohammed S.M. Elbaz may publish in the future.

Co-authorship network of co-authors of Mohammed S.M. Elbaz

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammed S.M. Elbaz. A scholar is included among the top collaborators of Mohammed S.M. Elbaz 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 Mohammed S.M. Elbaz. Mohammed S.M. Elbaz 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

1.

Elbaz, Mohammed S.M., et al.. (2025). Evaluating foundational 'segment anything' (Med-SAM1, Med-SAM2) deep learning models for left atrial segmentation in 3d LGE CMR. Journal of Cardiovascular Magnetic Resonance. 27. 101517–101517.

2.

Pradella, Maurice, Mohammed S.M. Elbaz, Daniel Lee, et al.. (2025). A comprehensive evaluation of the left atrium using cardiovascular magnetic resonance. Journal of Cardiovascular Magnetic Resonance. 27(1). 101852–101852. 3 indexed citations

3.

Elbaz, Mohammed S.M., Melika Shafeghat, Benjamin H. Freed, et al.. (2024). 3D Vortex‐Energetics in the Left Pulmonary Artery for Differentiating Pulmonary Arterial Hypertension and Pulmonary Venous Hypertension Groups Using 4D Flow MRI. Journal of Magnetic Resonance Imaging. 61(5). 2130–2143. 1 indexed citations

4.

Rajagopal, Sudarshan, Harm Jan Bogaard, Mohammed S.M. Elbaz, et al.. (2024). Emerging multimodality imaging techniques for the pulmonary circulation. European Respiratory Journal. 64(4). 2401128–2401128. 10 indexed citations

5.

Kholmovski, Eugene, et al.. (2024). Novel Self-Calibrated Threshold-Free Probabilistic Fibrosis Signature Technique for 3D Late Gadolinium Enhancement MRI. IEEE Transactions on Biomedical Engineering. 72(3). 856–869. 11 indexed citations

6.

Pradella, Maurice, et al.. (2023). MRI Quantification of Left Atrial Circumferential Strain in Mitral Regurgitation: A Feasibility and Reproducibility Study. Journal of Magnetic Resonance Imaging. 60(3). 988–998. 2 indexed citations

7.

Pradella, Maurice, et al.. (2023). Robust and fast stochastic 4D flow vector-field signature technique for quantifying composite flow dynamics from 4D flow MRI: Application to left atrial flow in atrial fibrillation. Medical Image Analysis. 92. 103065–103065. 4 indexed citations

8.

Salman, Ahmed, Mohamed Abdalla Salman, Mohammed S.M. Elbaz, et al.. (2022). Albuminuria as a predictor of mortality in type II diabetic patients after living-donor liver transplantation. Annals of Medicine. 54(1). 2597–2604. 3 indexed citations

9.

Berhane, Haben, Michael Scott, Mohammed S.M. Elbaz, et al.. (2020). Fully automated 3D aortic segmentation of 4D flow MRI for hemodynamic analysis using deep learning. Magnetic Resonance in Medicine. 84(4). 2204–2218. 95 indexed citations

10.

Markl, Michael, et al.. (2020). Intracardiac and Vascular Hemodynamics with Cardiovascular Magnetic Resonance in Heart Failure. Heart Failure Clinics. 17(1). 135–147. 4 indexed citations

11.

Zhong, Liang, Eric Schrauben, Julio García, et al.. (2019). Intracardiac 4D Flow MRI in Congenital Heart Disease: Recommendations on Behalf of the ISMRM Flow & Motion Study Group. Journal of Magnetic Resonance Imaging. 50(3). 677–681. 38 indexed citations

12.

Zhong, Liang, Eric Schrauben, Julio García, et al.. (2019). Intracardiac 4D Flow MRI in Congenital Heart Disease: Recommendations on Behalf of the ISMRM Flow & Motion Study Group. Journal of Magnetic Resonance Imaging. 50(3). 25 indexed citations

13.

Kamphuis, Vivian P., Mohammed S.M. Elbaz, Peter J. Boogaard, et al.. (2019). Stress increases intracardiac 4D flow cardiovascular magnetic resonance -derived energetics and vorticity and relates to VO2max in Fontan patients. Journal of Cardiovascular Magnetic Resonance. 21(1). 43–43. 19 indexed citations

14.

Garg, Pankaj, Peter Swoboda, Graham Fent, et al.. (2018). Left ventricular blood flow kinetic energy after myocardial infarction - insights from 4D flow cardiovascular magnetic resonance. Journal of Cardiovascular Magnetic Resonance. 20(1). 61–61. 70 indexed citations

15.

Kamphuis, Vivian P., Mohammed S.M. Elbaz, Peter J. Boogaard, et al.. (2018). Disproportionate intraventricular viscous energy loss in Fontan patients: analysis by 4D flow MRI. European Heart Journal - Cardiovascular Imaging. 20(3). 323–333. 33 indexed citations

16.

Elbaz, Mohammed S.M., et al.. (2017). Clinical applications of intra-cardiac four-dimensional flow cardiovascular magnetic resonance: A systematic review. International Journal of Cardiology. 249. 486–493. 56 indexed citations

17.

Garg, Pankaj, Jos J.M. Westenberg, Peter J. Boogaard, et al.. (2017). Comparison of fast acquisition strategies in whole‐heart four‐dimensional flow cardiac MR: Two‐center, 1.5 Tesla, phantom and in vivo validation study. Journal of Magnetic Resonance Imaging. 47(1). 272–281. 46 indexed citations

18.

Elbaz, Mohammed S.M., Rob J. van der Geest, Emmeline E. Calkoen, et al.. (2016). Assessment of viscous energy loss and the association with three‐dimensional vortex ring formation in left ventricular inflow: In vivo evaluation using four‐dimensional flow MRI. Magnetic Resonance in Medicine. 77(2). 794–805. 100 indexed citations

19.

Calkoen, Emmeline E., Mohammed S.M. Elbaz, Jos J.M. Westenberg, et al.. (2015). Altered left ventricular vortex ring formation by 4-dimensional flow magnetic resonance imaging after repair of atrioventricular septal defects. Journal of Thoracic and Cardiovascular Surgery. 150(5). 1233–1240.e1. 21 indexed citations

20.

Elbaz, Mohammed S.M. & Ahmed S. Fahmy. (2012). Active Shape Model with Inter-profile Modeling Paradigm for Cardiac Right Ventricle Segmentation. Lecture notes in computer science. 15(Pt 1). 691–698. 15 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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