Ivan S. Klyuzhin

902 total citations
49 papers, 588 citations indexed

About

Ivan S. Klyuzhin is a scholar working on Radiology, Nuclear Medicine and Imaging, Neurology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Ivan S. Klyuzhin has authored 49 papers receiving a total of 588 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Radiology, Nuclear Medicine and Imaging, 14 papers in Neurology and 10 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Ivan S. Klyuzhin's work include Radiomics and Machine Learning in Medical Imaging (23 papers), Medical Imaging Techniques and Applications (19 papers) and Parkinson's Disease Mechanisms and Treatments (12 papers). Ivan S. Klyuzhin is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (23 papers), Medical Imaging Techniques and Applications (19 papers) and Parkinson's Disease Mechanisms and Treatments (12 papers). Ivan S. Klyuzhin collaborates with scholars based in Canada, United States and Iran. Ivan S. Klyuzhin's co-authors include Arman Rahmim, Vesna Sossi, Mohammad R. Salmanpour, Abdollah Saberi, Mojtaba Shamsaei, Gerald H. Pollack, Jing Tang, Irène Buvat, Fanny Orlhac and Stephan Blinder and has published in prestigious journals such as Environmental Science & Technology, PLoS ONE and The Journal of Physical Chemistry B.

In The Last Decade

Ivan S. Klyuzhin

45 papers receiving 582 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 S. Klyuzhin Canada 14 333 160 106 84 69 49 588
Refaat E. Gabr United States 18 422 1.3× 70 0.4× 86 0.8× 47 0.6× 33 0.5× 54 809
Arun Joseph Germany 18 395 1.2× 74 0.5× 65 0.6× 58 0.7× 68 1.0× 44 765
Amir Fazlollahi Australia 13 204 0.6× 110 0.7× 62 0.6× 152 1.8× 78 1.1× 43 653
M. Louis Lauzon Canada 14 567 1.7× 221 1.4× 47 0.4× 29 0.3× 115 1.7× 37 998
Boubakeur Belaroussi France 10 426 1.3× 133 0.8× 55 0.5× 41 0.5× 59 0.9× 19 806
Esin Öztürk-Işık Türkiye 16 479 1.4× 52 0.3× 45 0.4× 27 0.3× 55 0.8× 54 655
Sagar Buch United States 16 832 2.5× 244 1.5× 80 0.8× 37 0.4× 106 1.5× 35 1.2k
Maria Gabriela Figueiró Longo United States 14 291 0.9× 61 0.4× 30 0.3× 68 0.8× 35 0.5× 34 466
Sarah Eskreis‐Winkler United States 12 447 1.3× 108 0.7× 35 0.3× 22 0.3× 38 0.6× 33 617
M. Ethan MacDonald Canada 12 250 0.8× 77 0.5× 45 0.4× 20 0.2× 77 1.1× 38 514

Countries citing papers authored by Ivan S. Klyuzhin

Since Specialization
Citations

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

Fields of papers citing papers by Ivan S. Klyuzhin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ivan S. Klyuzhin

This figure shows the co-authorship network connecting the top 25 collaborators of Ivan S. Klyuzhin. A scholar is included among the top collaborators of Ivan S. Klyuzhin 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 S. Klyuzhin. Ivan S. Klyuzhin 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.
Yousefirizi, Fereshteh, Weina Jin, Ian L. Alberts, et al.. (2025). Physician-in-the-Loop Active Learning in Radiology Artificial Intelligence Workflows: Opportunities, Challenges, and Future Directions. American Journal of Roentgenology. 225(5). e2533364–e2533364.
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Yousefirizi, Fereshteh, Ivan S. Klyuzhin, R. Petter Tonseth, et al.. (2024). Evaluating Outcome Prediction via Baseline, End-of-Treatment, and Delta Radiomics on PET-CT Images of Primary Mediastinal Large B-Cell Lymphoma. Cancers. 16(6). 1090–1090. 13 indexed citations
4.
Yousefirizi, Fereshteh, Ivan S. Klyuzhin, Joo Hyun O, et al.. (2024). TMTV-Net: fully automated total metabolic tumor volume segmentation in lymphoma PET/CT images — a multi-center generalizability analysis. European Journal of Nuclear Medicine and Molecular Imaging. 51(7). 1937–1954. 20 indexed citations
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Klyuzhin, Ivan S., et al.. (2023). PSMA‐Hornet: Fully‐automated, multi‐target segmentation of healthy organs in PSMA PET/CT images. Medical Physics. 51(2). 1203–1216. 7 indexed citations
7.
Fu, Jessie Fanglu, Ivan S. Klyuzhin, Julia G. Mannheim, et al.. (2022). Spatiotemporal patterns of putaminal dopamine processing in Parkinson’s disease: A multi-tracer positron emission tomography study. NeuroImage Clinical. 36. 103246–103246. 3 indexed citations
8.
Klyuzhin, Ivan S., Yixi Xu, Anthony Ortiz, et al.. (2022). Testing the Ability of Convolutional Neural Networks to Learn Radiomic Features. Computer Methods and Programs in Biomedicine. 219. 106750–106750. 13 indexed citations
9.
Black, David, et al.. (2021). Design of an anthropomorphic PET phantom with elastic lungs and respiration modeling. Medical Physics. 48(8). 4205–4217. 9 indexed citations
10.
Orlhac, Fanny, Christophe Nioche, Ivan S. Klyuzhin, Arman Rahmim, & Irène Buvat. (2021). Radiomics in PET Imaging. PET Clinics. 16(4). 597–612. 51 indexed citations
11.
Ma, Kevin, Stephanie A. Harmon, Ivan S. Klyuzhin, Arman Rahmim, & Barış Türkbey. (2021). Clinical Application of Artificial Intelligence in Positron Emission Tomography: Imaging of Prostate Cancer. PET Clinics. 17(1). 137–143. 7 indexed citations
12.
Salmanpour, Mohammad R., Mojtaba Shamsaei, Abdollah Saberi, et al.. (2020). Machine learning methods for optimal prediction of motor outcome in Parkinson’s disease. Physica Medica. 69. 233–240. 35 indexed citations
13.
Cheng, Ju-Chieh, et al.. (2020). A Monte Carlo approach for improving transient dopamine release detection sensitivity. Journal of Cerebral Blood Flow & Metabolism. 41(1). 116–131. 7 indexed citations
14.
Tang, Jing, Bao Yang, Ivan S. Klyuzhin, et al.. (2019). Artificial Neural Network–Based Prediction of Outcome in Parkinson’s Disease Patients Using DaTscan SPECT Imaging Features. Molecular Imaging and Biology. 21(6). 1165–1173. 40 indexed citations
15.
Sossi, Vesna, Ju-Chieh Cheng, & Ivan S. Klyuzhin. (2018). Imaging in Neurodegeneration: Movement Disorders. IEEE Transactions on Radiation and Plasma Medical Sciences. 3(3). 262–274. 3 indexed citations
16.
Salmanpour, Mohammad R., Mojtaba Shamsaei, Abdollah Saberi, et al.. (2018). Machine Learning Methods for Optimal Prediction of Outcome in Parkinson’s Disease. 1–5. 11 indexed citations
17.
Klyuzhin, Ivan S., Jessie Fanglu Fu, Matthew Sacheli, et al.. (2018). Data-driven, voxel-based analysis of brain PET images: Application of PCA and LASSO methods to visualize and quantify patterns of neurodegeneration. PLoS ONE. 13(11). e0206607–e0206607. 12 indexed citations
18.
Klyuzhin, Ivan S. & Vesna Sossi. (2017). PET Image Reconstruction and Deformable Motion Correction Using Unorganized Point Clouds. IEEE Transactions on Medical Imaging. 36(6). 1263–1275. 8 indexed citations
19.
Rahmim, Arman, Yousef Salimpour, Saurabh Jain, et al.. (2016). Application of texture analysis to DAT SPECT imaging: Relationship to clinical assessments. NeuroImage Clinical. 12. e1–e9. 55 indexed citations
20.
Blinder, Stephan, Ivan S. Klyuzhin, Marjorie Gonzalez, Arman Rahmim, & Vesna Sossi. (2014). Texture and shape analysis on high and low spatial resolution emission images. 1–6. 9 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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