Panagiotis Papadimitroulas

2.1k total citations · 1 hit paper
47 papers, 1.2k citations indexed

About

Panagiotis Papadimitroulas is a scholar working on Radiology, Nuclear Medicine and Imaging, Radiation and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Panagiotis Papadimitroulas has authored 47 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Radiology, Nuclear Medicine and Imaging, 24 papers in Radiation and 21 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Panagiotis Papadimitroulas's work include Medical Imaging Techniques and Applications (22 papers), Advanced Radiotherapy Techniques (20 papers) and Radiation Therapy and Dosimetry (17 papers). Panagiotis Papadimitroulas is often cited by papers focused on Medical Imaging Techniques and Applications (22 papers), Advanced Radiotherapy Techniques (20 papers) and Radiation Therapy and Dosimetry (17 papers). Panagiotis Papadimitroulas collaborates with scholars based in Greece, United States and France. Panagiotis Papadimitroulas's co-authors include George C. Kagadis, George Loudos, Dimitris Visvikis, George Loudos, David Sarrut, Thibault Mauxion, U. Pietrzyk, N. Freud, Charlotte Robert and Irène Buvat and has published in prestigious journals such as Journal of Medicinal Chemistry, Physics in Medicine and Biology and Medical Physics.

In The Last Decade

Panagiotis Papadimitroulas

41 papers receiving 1.2k citations

Hit Papers

A review of the use and potential of the GATE Monte Carlo... 2014 2026 2018 2022 2014 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A review of the use and potential of the GATE Monte Carlo simulation code for radiation therapy and dosimetry applications
    2014 388 citations David Sarrut, Manuel Bardiès et al. Medical Physics profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Panagiotis Papadimitroulas Greece 15 669 569 522 294 95 47 1.2k
Martin Carolan Australia 20 422 0.6× 623 1.1× 671 1.3× 171 0.6× 33 0.3× 74 1.4k
Zhi Chen China 21 597 0.9× 249 0.4× 389 0.7× 185 0.6× 63 0.7× 81 1.3k
Eirik Malinen Norway 27 1.1k 1.6× 672 1.2× 883 1.7× 200 0.7× 234 2.5× 138 2.4k
Mohammad Hussein United Kingdom 21 721 1.1× 723 1.3× 1.1k 2.1× 276 0.9× 86 0.9× 77 1.5k
Se Byeong Lee South Korea 19 386 0.6× 809 1.4× 902 1.7× 133 0.5× 29 0.3× 95 1.2k
Rongxiao Zhang United States 29 1.1k 1.7× 1.4k 2.5× 1.7k 3.3× 546 1.9× 74 0.8× 100 2.4k
Daniel C. Fernandez United States 16 364 0.5× 399 0.7× 157 0.3× 184 0.6× 33 0.3× 48 1.4k
P. Karaiskos Greece 30 1.6k 2.4× 1.6k 2.8× 2.1k 4.0× 591 2.0× 103 1.1× 145 2.5k
C. Ross Schmidtlein United States 19 1.3k 1.9× 652 1.1× 804 1.5× 405 1.4× 33 0.3× 77 1.7k
Edmond Sterpin Belgium 26 1.3k 1.9× 1.7k 3.0× 1.9k 3.7× 350 1.2× 41 0.4× 152 2.5k

Countries citing papers authored by Panagiotis Papadimitroulas

Since Specialization
Citations

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

Fields of papers citing papers by Panagiotis Papadimitroulas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Panagiotis Papadimitroulas

This figure shows the co-authorship network connecting the top 25 collaborators of Panagiotis Papadimitroulas. A scholar is included among the top collaborators of Panagiotis Papadimitroulas 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 Panagiotis Papadimitroulas. Panagiotis Papadimitroulas 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.
Bliznakov, Zhivko, Valentina Petkova, Panagiotis Papadimitroulas, et al.. (2025). Assessment of physical phantoms produced in the PHENOMENO project utilizing three fused filament fabrication approaches. Physica Medica. 136. 105061–105061.
2.
Παπαθανασίου, Νικόλαος, David Sarrut, Panagiotis Papadimitroulas, et al.. (2023). A radiomic‐ and dosiomic‐based machine learning regression model for pretreatment planning in 177Lu‐DOTATATE therapy. Medical Physics. 50(11). 7222–7235. 15 indexed citations
3.
Papadimitroulas, Panagiotis, Konstantinos Katsanos, D. Apostolopoulos, et al.. (2021). Clinical Evaluation of a Three-Dimensional Internal Dosimetry Technique for Liver Radioembolization with 90 Y Microspheres Using Dose Voxel Kernels. Cancer Biotherapy and Radiopharmaceuticals. 36(10). 809–819. 7 indexed citations
4.
Chatzipapas, Konstantinos, Panagiotis Papadimitroulas, Julien Bert, et al.. (2021). Standardization and Validation of Brachytherapy Seeds’ Modelling Using GATE and GGEMS Monte Carlo Toolkits. Cancers. 13(21). 5315–5315. 2 indexed citations
5.
Papadimitroulas, Panagiotis, Neo Christopher Chung, Franck Vermet, et al.. (2021). Artificial intelligence: Deep learning in oncological radiomics and challenges of interpretability and data harmonization. Physica Medica. 83. 108–121. 144 indexed citations
6.
Kagadis, George C., Ilias Gatos, Stavros Tsantis, et al.. (2020). Deep learning networks on chronic liver disease assessment with fine-tuning of shear wave elastography image sequences. Physics in Medicine and Biology. 65(21). 215027–215027. 19 indexed citations
7.
Papadimitroulas, Panagiotis, et al.. (2019). Size-specific dose estimations for pediatric chest, abdomen/pelvis and head CT scans with the use of GATE. Physica Medica. 65. 181–190. 14 indexed citations
8.
Papadimitroulas, Panagiotis, Konstantinos Chatzipapas, Dimitris Visvikis, et al.. (2018). A Review on Personalized Pediatric Dosimetry Applications Using Advanced Computational Tools. IEEE Transactions on Radiation and Plasma Medical Sciences. 3(6). 607–620. 10 indexed citations
9.
Papadimitroulas, Panagiotis, et al.. (2018). A personalized, Monte Carlo‐based method for internal dosimetric evaluation of radiopharmaceuticals in children. Medical Physics. 45(8). 3939–3949. 18 indexed citations
10.
Papadimitroulas, Panagiotis. (2017). Dosimetry applications in GATE Monte Carlo toolkit. Physica Medica. 41. 136–140. 47 indexed citations
11.
Papadimitroulas, Panagiotis, et al.. (2016). A PET/SPECT/X-ray prototype for whole body mouse imaging. Physica Medica. 32. 256–256. 1 indexed citations
12.
Papadimitroulas, Panagiotis, et al.. (2016). Pediatric nuclear medicine dosimetry: A monte carlo study on S-value variability due to patient specific characteristics. Physica Medica. 32. 240–240. 2 indexed citations
13.
Spirou, Spiridon V., et al.. (2015). Investigation of attenuation correction in SPECT using textural features, Monte Carlo simulations, and computational anthropomorphic models. Nuclear Medicine Communications. 36(9). 952–961. 1 indexed citations
14.
Sarrut, David, Manuel Bardiès, N. Freud, et al.. (2014). A review of the use and potential of the GATE Monte Carlo simulation code for radiation therapy and dosimetry applications. Medical Physics. 41(6Part1). 64301–64301. 388 indexed citations breakdown →
15.
Papadimitroulas, Panagiotis, George Loudos, Mathieu Hatt, et al.. (2013). Investigation of realistic PET simulations incorporating tumor patientˈs specificity using anthropomorphic models: Creation of an oncology database. Medical Physics. 40(11). 112506–112506. 21 indexed citations
16.
Kagadis, George C., Christos Kloukinas, Kevin L. Moore, et al.. (2013). Cloud computing in medical imaging. Medical Physics. 40(7). 70901–70901. 93 indexed citations
17.
Papadimitroulas, Panagiotis, et al.. (2012). SU‐E‐I‐88: Realistic Pathological Simulations of the NCAT and Zubal Anthropomorphic Models, Based on Clinical PET/CT Data. Medical Physics. 39(6Part5). 3645–3645. 1 indexed citations
18.
Papadimitroulas, Panagiotis, George Loudos, George Nikiforidis, & George C. Kagadis. (2012). A dose point kernel database using GATE Monte Carlo simulation toolkit for nuclear medicine applications: Comparison with other Monte Carlo codes. Medical Physics. 39(8). 5238–5247. 74 indexed citations
19.
Papadimitroulas, Panagiotis, et al.. (2011). Photon dose kernels dataset for nuclear medicine dosimetry, using the GATE Monte Carlo toolkit. University of Thessaly Institutional Repository (University of Thessaly). 35. 1390–1394. 2 indexed citations
20.
Loudos, George, et al.. (2010). Development and evaluation of QSPECT open-source software for the iterative reconstruction of SPECT images. Nuclear Medicine Communications. 31(6). 558–566. 10 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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