Cihat Eldeniz

900 total citations
40 papers, 540 citations indexed

About

Cihat Eldeniz is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics and Orthopedics and Sports Medicine. According to data from OpenAlex, Cihat Eldeniz has authored 40 papers receiving a total of 540 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Radiology, Nuclear Medicine and Imaging, 10 papers in Genetics and 7 papers in Orthopedics and Sports Medicine. Recurrent topics in Cihat Eldeniz's work include Advanced MRI Techniques and Applications (21 papers), Medical Imaging Techniques and Applications (15 papers) and Hemoglobinopathies and Related Disorders (10 papers). Cihat Eldeniz is often cited by papers focused on Advanced MRI Techniques and Applications (21 papers), Medical Imaging Techniques and Applications (15 papers) and Hemoglobinopathies and Related Disorders (10 papers). Cihat Eldeniz collaborates with scholars based in United States, Germany and China. Cihat Eldeniz's co-authors include Hongyu An, Yasheng Chen, Jin‐Moo Lee, Andria L. Ford, Ulugbek S. Kamilov, Jiaming Liu, Michael M. Binkley, Kristin P. Guilliams, Melanie E. Fields and Dustin K. Ragan and has published in prestigious journals such as Blood, PLoS ONE and Neurology.

In The Last Decade

Cihat Eldeniz

38 papers receiving 534 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cihat Eldeniz United States 12 250 235 119 86 68 40 540
Dustin K. Ragan United States 14 226 0.9× 288 1.2× 151 1.3× 105 1.2× 132 1.9× 28 607
Samir D. Sharma United States 14 460 1.8× 50 0.2× 40 0.3× 31 0.4× 11 0.2× 25 846
Hendrik Laue Germany 13 559 2.2× 46 0.2× 42 0.4× 35 0.4× 9 0.1× 26 884
Chaitra Badve United States 18 782 3.1× 149 0.6× 10 0.1× 11 0.1× 51 0.8× 42 996
Yihao Guo China 12 345 1.4× 28 0.1× 16 0.1× 49 0.6× 13 0.2× 43 512
Philip J. Beatty United States 11 573 2.3× 21 0.1× 16 0.1× 100 1.2× 17 0.3× 13 940
Vivek Sehgal United States 11 566 2.3× 114 0.5× 15 0.1× 12 0.1× 65 1.0× 15 1.1k
Christopher Beaulieu United States 7 771 3.1× 21 0.1× 12 0.1× 143 1.7× 15 0.2× 8 1.2k
K. Eberhardt Germany 14 139 0.6× 16 0.1× 57 0.5× 5 0.1× 13 0.2× 31 622
Jianlin Wu China 7 540 2.2× 17 0.1× 14 0.1× 9 0.1× 46 0.7× 21 763

Countries citing papers authored by Cihat Eldeniz

Since Specialization
Citations

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

Fields of papers citing papers by Cihat Eldeniz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cihat Eldeniz

This figure shows the co-authorship network connecting the top 25 collaborators of Cihat Eldeniz. A scholar is included among the top collaborators of Cihat Eldeniz 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 Cihat Eldeniz. Cihat Eldeniz 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.
Eldeniz, Cihat, Thomas H. Schindler, Linda R. Peterson, et al.. (2025). Model‐based self‐supervised learning for quantitative assessment of myocardial oxygen extraction fraction and myocardial blood volume. Magnetic Resonance in Medicine. 94(4). 1793–1803. 1 indexed citations
2.
Baldelomar, Edwin J., Darya Morozov, Leslie Dawn Wilson, et al.. (2024). Resting-state MRI reveals spontaneous physiological fluctuations in the kidney and tracks diabetic nephropathy in rats. American Journal of Physiology-Renal Physiology. 327(1). F113–F127. 1 indexed citations
3.
Eldeniz, Cihat, et al.. (2024). SPICER: Self‐supervised learning for MRI with automatic coil sensitivity estimation and reconstruction. Magnetic Resonance in Medicine. 92(3). 1048–1063. 9 indexed citations
4.
Eldeniz, Cihat, Thomas H. Schindler, Qi Huang, et al.. (2024). Quantification of myocardial oxygen extraction fraction on noncontrast MRI enabled by deep learning. PubMed. 1(4). 1 indexed citations
5.
Eldeniz, Cihat, Yasheng Chen, Gary B. Skolnick, et al.. (2024). MR Cranial Bone Imaging: Evaluation of Both Motion-Corrected and Automated Deep Learning Pseudo-CT Estimated MR Images. American Journal of Neuroradiology. 45(9). 1284–1290. 3 indexed citations
6.
Eldeniz, Cihat, et al.. (2023). Self-Supervised Deep Equilibrium Models With Theoretical Guarantees and Applications to MRI Reconstruction. IEEE Transactions on Computational Imaging. 9. 796–807. 8 indexed citations
7.
Eldeniz, Cihat, Paul K. Commean, Yan Yan, et al.. (2023). Motion-corrected radial head MRI without any navigator, data redundancy or external tracking. Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition. 1 indexed citations
8.
Chen, Sihao, Tyler J. Fraum, Cihat Eldeniz, et al.. (2023). MR-Assisted PET Respiratory Motion Correction Using Deep-Learning Based Short-Scan Motion Fields. Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition. 1 indexed citations
9.
Sun, Yu, et al.. (2022). Deformation-Compensated Learning for Image Reconstruction Without Ground Truth. IEEE Transactions on Medical Imaging. 41(9). 2371–2384. 9 indexed citations
10.
Hulbert, Monica L., Melanie E. Fields, Kristin P. Guilliams, et al.. (2022). Normalization of cerebral hemodynamics after hematopoietic stem cell transplant in children with sickle cell disease. Blood. 141(4). 335–344. 16 indexed citations
11.
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13.
Eldeniz, Cihat, Hongyu An, Yang Yang, et al.. (2021). Quantification of myocardial oxygen extraction fraction: A proof‐of‐concept study. Magnetic Resonance in Medicine. 85(6). 3318–3325. 6 indexed citations
14.
Guilliams, Kristin P., Melanie E. Fields, Dustin K. Ragan, et al.. (2017). Red cell exchange transfusions lower cerebral blood flow and oxygen extraction fraction in pediatric sickle cell anemia. Blood. 131(9). 1012–1021. 65 indexed citations
15.
Hulbert, Monica L., Kristin P. Guilliams, Melanie E. Fields, et al.. (2017). Normalization of Cerebral Hemodynamics after Hematopoietic Stem Cell Transplant in Children with Sickle Cell Anemia. Blood. 130. 2245–2245. 3 indexed citations
16.
Guilliams, Kristin P., Melanie E. Fields, Dustin K. Ragan, et al.. (2016). Large-Vessel Vasculopathy in Children With Sickle Cell Disease: A Magnetic Resonance Imaging Study of Infarct Topography and Focal Atrophy. Pediatric Neurology. 69. 49–57. 38 indexed citations
17.
Ramalho, Joana, et al.. (2016). Comparison of Cerebral Blood Volume and Plasma Volume in Untreated Intracranial Tumors. PLoS ONE. 11(9). e0161807–e0161807. 11 indexed citations
18.
Yuan, Hong, Jonathan E. Frank, Hongyu An, et al.. (2013). Spatiotemporal Uptake Characteristics of [ 18 ]F-2-Fluoro-2-Deoxy- d -Glucose in a Rat Middle Cerebral Artery Occlusion Model. Stroke. 44(8). 2292–2299. 16 indexed citations
19.
An, Hongyu, Qingwei Liu, Cihat Eldeniz, & Weili Lin. (2011). Absolute Oxygenation Metabolism Measurements Using Magnetic Resonance Imaging. PubMed. 5(1). 120–135. 2 indexed citations
20.
Marcia, Roummel F., Changsoon Kim, Cihat Eldeniz, et al.. (2008). Superimposed video disambiguation for increased field of view. Optics Express. 16(21). 16352–16352. 13 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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