Mathias Prokop

38.2k total citations · 6 hit papers
465 papers, 19.9k citations indexed

About

Mathias Prokop is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Biomedical Engineering. According to data from OpenAlex, Mathias Prokop has authored 465 papers receiving a total of 19.9k indexed citations (citations by other indexed papers that have themselves been cited), including 254 papers in Radiology, Nuclear Medicine and Imaging, 243 papers in Pulmonary and Respiratory Medicine and 100 papers in Biomedical Engineering. Recurrent topics in Mathias Prokop's work include Lung Cancer Diagnosis and Treatment (118 papers), Advanced X-ray and CT Imaging (87 papers) and Radiomics and Machine Learning in Medical Imaging (83 papers). Mathias Prokop is often cited by papers focused on Lung Cancer Diagnosis and Treatment (118 papers), Advanced X-ray and CT Imaging (87 papers) and Radiomics and Machine Learning in Medical Imaging (83 papers). Mathias Prokop collaborates with scholars based in Netherlands, Germany and United States. Mathias Prokop's co-authors include Bram van Ginneken, Cornelia Schaefer‐Prokop, Hester A. Gietema, Ernst T. Scholten, Arnold M. R. Schilham, Bartjan de Hoop, Matthijs Oudkerk, Harry J. de Koning, Rob J. van Klaveren and Ingrid C. Sluimer and has published in prestigious journals such as JAMA, Circulation and SHILAP Revista de lepidopterología.

In The Last Decade

Mathias Prokop

442 papers receiving 19.3k citations

Hit Papers

Guidelines for Management... 2006 2026 2012 2019 2017 2008 2015 2020 2006 500 1000 1.5k
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. Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017
    2017 1.5k citations Yoshiharu Ohno, Mathias Prokop et al. Radiology profile →
  2. Diagnostic Accuracy of 64-Slice Computed Tomography Coronary Angiography
    2008 838 citations Joanne D. Schuijf, Mathias Prokop et al. profile →
  3. British Thoracic Society guidelines for the investigation and management of pulmonary nodules: accredited by NICE
    2015 604 citations Mathias Prokop et al. profile →
  4. CO-RADS: A Categorical CT Assessment Scheme for Patients Suspected of Having COVID-19—Definition and Evaluation
    2020 550 citations Mathias Prokop, Wouter M. van Everdingen et al. Radiology profile →
  5. Computer analysis of computed tomography scans of the lung: a survey
    2006 389 citations Mathias Prokop, Bram van Ginneken et al. profile →
  6. Comprehensive Health Assessment 3 Months After Recovery From Acute Coronavirus Disease 2019 (COVID-19)
    2020 325 citations Monique Brink, Mathias Prokop et al. profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Mathias Prokop 10.6k 10.4k 3.7k 2.7k 1.9k 465 19.9k
Hans‐Ulrich Kauczor 10.4k 1.0× 10.4k 1.0× 3.7k 1.0× 4.3k 1.6× 2.3k 1.2× 934 25.6k
Geoffrey D. Rubin 7.5k 0.7× 6.7k 0.6× 3.3k 0.9× 3.8k 1.4× 2.7k 1.4× 228 14.0k
Bernd Hamm 9.5k 0.9× 4.8k 0.5× 4.1k 1.1× 5.3k 1.9× 1.6k 0.8× 905 22.0k
Nancy A. Obuchowski 5.4k 0.5× 3.3k 0.3× 2.4k 0.6× 4.9k 1.8× 1.8k 0.9× 339 20.3k
Kaori Togashi 7.8k 0.7× 2.8k 0.3× 1.8k 0.5× 3.2k 1.2× 501 0.3× 561 20.1k
Hedvig Hricak 20.2k 1.9× 17.4k 1.7× 3.5k 0.9× 7.8k 2.9× 651 0.3× 629 39.8k
Luca Saba 3.8k 0.4× 5.0k 0.5× 1.2k 0.3× 1.8k 0.7× 3.9k 2.0× 580 11.8k
Joachim E. Wildberger 11.3k 1.1× 4.9k 0.5× 4.8k 1.3× 2.4k 0.9× 2.9k 1.5× 449 17.2k
Yasuyuki Yamashita 9.1k 0.9× 4.3k 0.4× 4.0k 1.1× 3.0k 1.1× 801 0.4× 620 16.4k
Elkan F. Halpern 7.9k 0.7× 6.5k 0.6× 3.9k 1.1× 6.0k 2.2× 3.8k 2.0× 329 24.2k

Countries citing papers authored by Mathias Prokop

Since Specialization
Citations

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

Fields of papers citing papers by Mathias Prokop

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mathias Prokop

This figure shows the co-authorship network connecting the top 25 collaborators of Mathias Prokop. A scholar is included among the top collaborators of Mathias Prokop 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 Mathias Prokop. Mathias Prokop 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.
Scholten, Ernst T., Ewoud J. Smit, Matthieu Rutten, et al.. (2025). The ULS23 challenge: A baseline model and benchmark dataset for 3D universal lesion segmentation in computed tomography. Medical Image Analysis. 102. 103525–103525. 3 indexed citations
2.
3.
Duiverman, Marieke L., Martijn D. de Kruif, Daniela E. Oprea‐Lager, et al.. (2025). [68Ga]FAPI PET/CT reveals increased pulmonary fibroblast activation protein expression in long COVID patients after ICU discharge. European Journal of Nuclear Medicine and Molecular Imaging. 53(1). 565–573. 1 indexed citations
4.
Schiebler, Mark L., Masahiro Jinzaki, Masahiro Yanagawa, et al.. (2025). Future Applications of Cardiothoracic CT. Radiology. 315(3). e240085–e240085.
5.
Smit, Ewoud J., et al.. (2024). Performance evaluation of a 4D similarity filter for dynamic CT angiography imaging of the liver. Medical Physics. 51(12). 8814–8827. 1 indexed citations
6.
Prokop, Mathias, Wouter M. van Everdingen, Henriëtte M. E. Quarles van Ufford, et al.. (2020). CO-RADS: A Categorical CT Assessment Scheme for Patients Suspected of Having COVID-19—Definition and Evaluation. Radiology. 296(2). E97–E104. 550 indexed citations breakdown →
7.
8.
Pegge, Sjoert, et al.. (2020). Cerebral Artery and Vein Segmentation in Four-dimensional CT Angiography Using Convolutional Neural Networks. Radiology Artificial Intelligence. 2(4). e190178–e190178. 12 indexed citations
9.
Meijer, Frederick J. A., et al.. (2020). Image-level detection of arterial occlusions in 4D-CTA of acute stroke patients using deep learning. Medical Image Analysis. 66. 101810–101810. 23 indexed citations
10.
Sedelaar, J.P. Michiel, et al.. (2020). The Effect of Higher Level Computerized Clinical Decision Support Systems on Oncology Care: A Systematic Review. Cancers. 12(4). 1032–1032. 47 indexed citations
11.
Tanabe, Yuki, Ewoud J. Smit, Teruhito Kido, et al.. (2020). Clinical application of four-dimensional noise reduction filtering with a similarity algorithm in dynamic myocardial computed tomography perfusion imaging. International journal of cardiac imaging. 36(9). 1781–1789. 10 indexed citations
12.
Grob, D., Ewoud J. Smit, Jip F. Prince, et al.. (2019). Iodine Maps from Subtraction CT or Dual-Energy CT to Detect Pulmonary Emboli with CT Angiography: A Multiple-Observer Study. Radiology. 292(1). 197–205. 38 indexed citations
13.
Meijer, Frederick J. A., et al.. (2019). Ultra-high-resolution subtraction CT angiography in the follow-up of treated intracranial aneurysms. Insights into Imaging. 10(1). 2–2. 24 indexed citations
14.
Pegge, Sjoert, Kazuhiro Murayama, Hieronymus D. Boogaarts, et al.. (2019). Color-Mapping of 4D-CTA for the Detection of Cranial Arteriovenous Shunts. American Journal of Neuroradiology. 40(9). 1498–1504. 2 indexed citations
15.
Patel, Ajay, Floris H.B.M. Schreuder, Catharina J.M. Klijn, et al.. (2019). Intracerebral Haemorrhage Segmentation in Non-Contrast CT. Scientific Reports. 9(1). 17858–17858. 41 indexed citations
16.
Kats‐Ugurlu, Gürsah, Carla van Herpen, Sasja F. Mulder, et al.. (2018). Pulmonary Lymphangitis Carcinomatosis of Clear Cell Renal Cell Carcinoma After Angiogenesis Inhibition. 1(2). 2 indexed citations
17.
Manniesing, Rashindra, Marcel T. H. Oei, Luuk J. Oostveen, et al.. (2017). White Matter and Gray Matter Segmentation in 4D Computed Tomography. Scientific Reports. 7(1). 119–119. 19 indexed citations
18.
Patel, Ajay, Mathias Prokop, Ewoud J. van Dijk, et al.. (2017). Robust Segmentation of the Full Cerebral Vasculature in 4D CT of Suspected Stroke Patients. Scientific Reports. 7(1). 15622–15622. 35 indexed citations
19.
Patel, Ajay, Bram van Ginneken, Frederick J. A. Meijer, et al.. (2016). Robust cranial cavity segmentation in CT and CT perfusion images of trauma and suspected stroke patients. Medical Image Analysis. 36. 216–228. 22 indexed citations
20.
Kortman, Hans, Ewoud J. Smit, Marcel T. H. Oei, et al.. (2014). 4D-CTA in Neurovascular Disease: A Review. American Journal of Neuroradiology. 36(6). 1026–1033. 83 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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