Eli Eikefjord

489 total citations
19 papers, 203 citations indexed

About

Eli Eikefjord is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Cognitive Neuroscience. According to data from OpenAlex, Eli Eikefjord has authored 19 papers receiving a total of 203 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Radiology, Nuclear Medicine and Imaging, 5 papers in Pulmonary and Respiratory Medicine and 3 papers in Cognitive Neuroscience. Recurrent topics in Eli Eikefjord's work include MRI in cancer diagnosis (13 papers), Advanced MRI Techniques and Applications (10 papers) and Advanced Neuroimaging Techniques and Applications (6 papers). Eli Eikefjord is often cited by papers focused on MRI in cancer diagnosis (13 papers), Advanced MRI Techniques and Applications (10 papers) and Advanced Neuroimaging Techniques and Applications (6 papers). Eli Eikefjord collaborates with scholars based in Norway, Poland and Netherlands. Eli Eikefjord's co-authors include Jarle Rørvik, Arvid Lundervold, Erlend Hodneland, Frits Thorsen, Erling Andersen, Einar Svarstad, Artur Klepaczko, Ole A. Andreassen, Ann‐Marie G. de Lange and Dani Beck and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and IEEE Transactions on Image Processing.

In The Last Decade

Eli Eikefjord

16 papers receiving 197 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eli Eikefjord Norway 9 145 47 44 41 25 19 203
Mahesh Keerthivasan United States 11 250 1.7× 58 1.2× 11 0.3× 47 1.1× 24 1.0× 43 316
Fábio Nery United Kingdom 7 165 1.1× 57 1.2× 26 0.6× 24 0.6× 6 0.2× 14 210
Martin Šámal Czechia 11 210 1.4× 98 2.1× 91 2.1× 48 1.2× 19 0.8× 26 350
Mrinalini Bhagawati India 6 50 0.3× 24 0.5× 45 1.0× 23 0.6× 19 0.8× 9 219
Juan Carlos López‐Azor Spain 8 51 0.4× 46 1.0× 21 0.5× 22 0.5× 47 1.9× 22 259
Alena Uus United Kingdom 10 86 0.6× 43 0.9× 183 4.2× 17 0.4× 13 0.5× 50 310
P.E. Colombo Italy 9 192 1.3× 88 1.9× 5 0.1× 112 2.7× 7 0.3× 27 278
Jesper Leth Hougaard Denmark 12 367 2.5× 14 0.3× 13 0.3× 100 2.4× 23 0.9× 18 518
Lydia Chougar France 10 101 0.7× 6 0.1× 19 0.4× 10 0.2× 17 0.7× 22 300

Countries citing papers authored by Eli Eikefjord

Since Specialization
Citations

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

Fields of papers citing papers by Eli Eikefjord

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eli Eikefjord

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

All Works

19 of 19 papers shown
1.
Korbmacher, Max, Didac Vidal‐Piñeiro, Mengyun Wang, et al.. (2025). Cross‐Sectional Brain Age Assessments Are Limited in Predicting Future Brain Change. Human Brain Mapping. 46(6). e70203–e70203. 2 indexed citations
2.
Korbmacher, Max, Dennis van der Meer, Dani Beck, et al.. (2024). Brain asymmetries from mid- to late life and hemispheric brain age. Nature Communications. 15(1). 956–956. 16 indexed citations
3.
Korbmacher, Max, Dennis van der Meer, Dani Beck, et al.. (2024). Distinct Longitudinal Brain White Matter Microstructure Changes and Associated Polygenic Risk of Common Psychiatric Disorders and Alzheimer’s Disease in the UK Biobank. SHILAP Revista de lepidopterología. 4(4). 100323–100323. 4 indexed citations
4.
Korbmacher, Max, Dennis van der Meer, Dani Beck, et al.. (2024). Brain asymmetries from midlife to old adulthood and hemispheric brain age. Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition.
5.
Korbmacher, Max, Ann‐Marie G. de Lange, Dennis van der Meer, et al.. (2023). Brain‐wide associations between white matter and age highlight the role of fornix microstructure in brain ageing. Human Brain Mapping. 44(10). 4101–4119. 17 indexed citations
6.
Korbmacher, Max, Tiril P. Gurholt, Ann‐Marie G. de Lange, et al.. (2023). Bio-psycho-social factors’ associations with brain age: a large-scale UK Biobank diffusion study of 35,749 participants. Frontiers in Psychology. 14. 1117732–1117732. 9 indexed citations
7.
Klepaczko, Artur, et al.. (2022). Whole kidney and renal cortex segmentation in contrast-enhanced MRI using a joint classification and segmentation convolutional neural network. Journal of Applied Biomedicine. 42(1). 295–311. 4 indexed citations
8.
Klepaczko, Artur, Eli Eikefjord, & Arvid Lundervold. (2021). Healthy Kidney Segmentation in the Dce-Mr Images Using a Convolutional Neural Network and Temporal Signal Characteristics. Sensors. 21(20). 6714–6714. 6 indexed citations
9.
Klepaczko, Artur, Michał Strzelecki, Marcin Kociołek, Eli Eikefjord, & Arvid Lundervold. (2020). A Multi-Layer Perceptron Network for Perfusion Parameter Estimation in DCE-MRI Studies of the Healthy Kidney. Applied Sciences. 10(16). 5525–5525. 9 indexed citations
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Klepaczko, Artur, Michał Strzelecki, Ludomir Stefańczyk, et al.. (2018). Numerical simulation of the b-SSFP sequence in MR perfusion-weighted imaging of the kidney. 292–297.
12.
Eikefjord, Eli, et al.. (2017). Workflow sensitivity of post-processing methods in renal DCE-MRI. Magnetic Resonance Imaging. 42. 60–68. 5 indexed citations
13.
Eikefjord, Eli, Erling Andersen, Erlend Hodneland, et al.. (2016). Quantification of Single-Kidney Function and Volume in Living Kidney Donors Using Dynamic Contrast-Enhanced MRI. American Journal of Roentgenology. 207(5). 1022–1030. 13 indexed citations
14.
Eikefjord, Eli, Erling Andersen, Erlend Hodneland, et al.. (2016). Dynamic contrast-enhanced MRI measurement of renal function in healthy participants. Acta Radiologica. 58(6). 748–757. 21 indexed citations
15.
Eikefjord, Eli, Erling Andersen, Erlend Hodneland, et al.. (2015). Use of 3D DCE-MRI for the Estimation of Renal Perfusion and Glomerular Filtration Rate: An Intrasubject Comparison of FLASH and KWIC With a Comprehensive Framework for Evaluation. American Journal of Roentgenology. 204(3). W273–W281. 24 indexed citations
16.
Hodneland, Erlend, et al.. (2014). Segmentation-Driven Image Registration-Application to 4D DCE-MRI Recordings of the Moving Kidneys. IEEE Transactions on Image Processing. 23(5). 2392–2404. 22 indexed citations
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Eikefjord, Eli, Frits Thorsen, & Jarle Rørvik. (2007). Comparison of Effective Radiation Doses in Patients Undergoing Unenhanced MDCT and Excretory Urography for Acute Flank Pain. American Journal of Roentgenology. 188(4). 934–939. 35 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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