Ivan Ezhov

3.3k total citations
43 papers, 331 citations indexed

About

Ivan Ezhov is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Mathematical Physics. According to data from OpenAlex, Ivan Ezhov has authored 43 papers receiving a total of 331 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Radiology, Nuclear Medicine and Imaging, 9 papers in Artificial Intelligence and 7 papers in Mathematical Physics. Recurrent topics in Ivan Ezhov's work include Radiomics and Machine Learning in Medical Imaging (6 papers), Advanced Queuing Theory Analysis (6 papers) and Optical Imaging and Spectroscopy Techniques (5 papers). Ivan Ezhov is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (6 papers), Advanced Queuing Theory Analysis (6 papers) and Optical Imaging and Spectroscopy Techniques (5 papers). Ivan Ezhov collaborates with scholars based in Germany, Switzerland and United Kingdom. Ivan Ezhov's co-authors include Bjoern Menze, A. V. Skorokhod, Benedikt Wiestler, Suprosanna Shit, Johannes C. Paetzold, Florian Kofler, Jana Lipková, Christoph Berger, Jan S. Kirschke and Claus Zimmer and has published in prestigious journals such as Nature Communications, Journal of Applied Physics and IEEE Transactions on Medical Imaging.

In The Last Decade

Ivan Ezhov

37 papers receiving 300 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ivan Ezhov Germany 9 127 63 60 43 40 43 331
Francisco J. López Spain 18 22 0.2× 32 0.5× 15 0.3× 46 1.1× 9 0.2× 80 824
Sergiy Pereverzyev Austria 8 25 0.2× 42 0.7× 22 0.4× 7 0.2× 1 0.0× 15 271
Maulik R. Kamdar United States 10 56 0.4× 150 2.4× 20 0.3× 1 0.0× 42 1.1× 24 300
Piotr Rudnicki Canada 11 97 0.8× 150 2.4× 12 0.2× 3 0.1× 9 0.2× 48 460
Przemysław Waliszewski Poland 16 52 0.4× 48 0.8× 29 0.5× 14 0.3× 3 0.1× 40 562
Yuanyuan Bao China 9 104 0.8× 97 1.5× 94 1.6× 3 0.1× 36 326
Shawn Andrews Canada 8 110 0.9× 122 1.9× 146 2.4× 70 1.6× 14 410
Vittorio Di Somma Italy 6 78 0.6× 109 1.7× 53 0.9× 5 0.1× 11 302
Julius Adebayo United States 6 103 0.8× 260 4.1× 68 1.1× 5 0.1× 10 462
Qianye Yang United Kingdom 11 118 0.9× 74 1.2× 98 1.6× 10 0.2× 4 0.1× 21 318

Countries citing papers authored by Ivan Ezhov

Since Specialization
Citations

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

Fields of papers citing papers by Ivan Ezhov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ivan Ezhov

This figure shows the co-authorship network connecting the top 25 collaborators of Ivan Ezhov. A scholar is included among the top collaborators of Ivan Ezhov 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 Ivan Ezhov. Ivan Ezhov 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.
Ezhov, Ivan, Petros Koumoutsakos, Tamaz Amiranashvili, et al.. (2025). Individualizing glioma radiotherapy planning by optimization of a data and physics-informed discrete loss. Nature Communications. 16(1). 5982–5982. 2 indexed citations
2.
Nicolini, Luis Fernando, et al.. (2025). Neural network surrogate and projected gradient descent for fast and reliable finite element model calibration: A case study on an intervertebral disc. Computers in Biology and Medicine. 186. 109646–109646. 1 indexed citations
3.
Zhang, Zirui, Ivan Ezhov, A. N. Zhu, et al.. (2024). Personalized predictions of Glioblastoma infiltration: Mathematical models, Physics-Informed Neural Networks and multimodal scans. Medical Image Analysis. 101. 103423–103423. 7 indexed citations
4.
He, Hailong, Johannes C. Paetzold, Ivan Ezhov, et al.. (2024). Machine Learning Analysis of Human Skin by Optoacoustic Mesoscopy for Automated Extraction of Psoriasis and Aging Biomarkers. IEEE Transactions on Medical Imaging. 43(6). 2074–2085. 7 indexed citations
5.
Lange, Frédéric, et al.. (2024). Digital instrument simulator to optimize the development of hyperspectral systems: application for intraoperative functional brain mapping. Journal of Biomedical Optics. 30(2). 23513–23513. 1 indexed citations
6.
Ezhov, Ivan, Frédéric Lange, Bruno Montcel, et al.. (2024). Transportable hyperspectral imaging setup based on fast, high-density spectral scanning for in situ quantitative biochemical mapping of fresh tissue biopsies. Journal of Biomedical Optics. 29(9). 93508–93508. 3 indexed citations
7.
Ezhov, Ivan, Florian Kofler, Jana Lipková, et al.. (2024). A Learnable Prior Improves Inverse Tumor Growth Modeling. IEEE Transactions on Medical Imaging. 44(3). 1297–1307. 3 indexed citations
8.
Ezhov, Ivan, Florian Kofler, Suprosanna Shit, et al.. (2024). Learnable real-time inference of molecular composition from diffuse spectroscopy of brain tissue. Journal of Biomedical Optics. 29(9). 93509–93509. 2 indexed citations
9.
Kofler, Florian, Ivan Ezhov, Fabian Isensee, et al.. (2023). Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient. Zurich Open Repository and Archive (University of Zurich). 2(May 2023). 27–71. 14 indexed citations
10.
Kofler, Florian, Ivan Ezhov, Sophia J. Wagner, et al.. (2023). Approaching Peak Ground Truth. PuSH - Publication Server of Helmholtz Zentrum München. 1–6. 4 indexed citations
11.
Ezhov, Ivan, Jan C. Peeken, Jana Lipková, et al.. (2023). Toward image-based personalization of glioblastoma therapy: A clinical and biological validation study of a novel, deep learning-driven tumor growth model. Neuro-Oncology Advances. 6(1). vdad171–vdad171. 2 indexed citations
12.
Menten, Martin J., Johannes C. Paetzold, Veronika A. Zimmer, et al.. (2023). A skeletonization algorithm for gradient-based optimization. 21337–21346. 6 indexed citations
13.
Ezhov, Ivan, Suprosanna Shit, Jana Lipková, et al.. (2022). Learn-Morph-Infer: A new way of solving the inverse problem for brain tumor modeling. Medical Image Analysis. 83. 102672–102672. 14 indexed citations
14.
Shit, Suprosanna, et al.. (2022). SRflow: Deep learning based super-resolution of 4D-flow MRI data. Frontiers in Artificial Intelligence. 5. 928181–928181. 14 indexed citations
15.
Kofler, Florian, Ivan Ezhov, Lucas Fidon, et al.. (2021). Robust, Primitive, and Unsupervised Quality Estimation for Segmentation Ensembles. Frontiers in Neuroscience. 15. 752780–752780. 2 indexed citations
16.
Kofler, Florian, Christoph Berger, Jana Lipková, et al.. (2020). BraTS Toolkit: Translating BraTS Brain Tumor Segmentation Algorithms Into Clinical and Scientific Practice. Frontiers in Neuroscience. 14. 125–125. 61 indexed citations
17.
Ezhov, Ivan, et al.. (2002). System G|Gκ|1 with Batch Service of Calls. Ukrainian Mathematical Journal. 54(4). 548–569. 3 indexed citations
18.
Ezhov, Ivan, et al.. (1993). Limit functionals for a semicontinuous difference of renewal processes with discrete time. Ukrainian Mathematical Journal. 45(12). 1924–1927. 1 indexed citations
19.
Ezhov, Ivan, et al.. (1975). On a Class of Branching Processes. Theory of Probability and Its Applications. 20(1). 180–185.
20.

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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