Fons van der Sommen

3.2k total citations · 1 hit paper
130 papers, 1.6k citations indexed

About

Fons van der Sommen is a scholar working on Surgery, Oncology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Fons van der Sommen has authored 130 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Surgery, 54 papers in Oncology and 49 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Fons van der Sommen's work include Esophageal Cancer Research and Treatment (50 papers), Colorectal Cancer Screening and Detection (47 papers) and Radiomics and Machine Learning in Medical Imaging (34 papers). Fons van der Sommen is often cited by papers focused on Esophageal Cancer Research and Treatment (50 papers), Colorectal Cancer Screening and Detection (47 papers) and Radiomics and Machine Learning in Medical Imaging (34 papers). Fons van der Sommen collaborates with scholars based in Netherlands, Belgium and Germany. Fons van der Sommen's co-authors include Erik J. Schoon, Peter H. N. de With, Wouter L. Curvers, Jacques Bergman, Svitlana Zinger, Maarten R. Struyvenberg, Joost van der Putten, Sveta Zinger, Raf Bisschops and Peter H. de With and has published in prestigious journals such as SHILAP Revista de lepidopterología, Gastroenterology and Gut.

In The Last Decade

Fons van der Sommen

111 papers receiving 1.6k citations

Hit Papers

Deep-Learning System Dete... 2019 2026 2021 2023 2019 50 100 150 200
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. Deep-Learning System Detects Neoplasia in Patients With Barrett’s Esophagus With Higher Accuracy Than Endoscopists in a Multistep Training and Validation Study With Benchmarking
    2019 229 citations Albert J. de Groof, Maarten R. Struyvenberg et al. Gastroenterology profile →

Author Peers

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

Author Last Decade Papers Cites
Fons van der Sommen 859 806 633 534 220 130 1.6k
Kazuharu Aoyama 1.3k 1.5× 949 1.2× 1.2k 2.0× 747 1.4× 331 1.5× 25 2.4k
Satoki Shichijo 1.8k 2.0× 1.4k 1.8× 1.1k 1.7× 608 1.1× 280 1.3× 119 2.7k
Xiaogang Liu 647 0.8× 227 0.3× 1.1k 1.7× 726 1.4× 419 1.9× 34 1.6k
Keigo Matsuo 481 0.6× 394 0.5× 509 0.8× 305 0.6× 148 0.7× 29 992
Masashi Misawa 1.4k 1.7× 859 1.1× 2.2k 3.5× 904 1.7× 457 2.1× 139 2.9k
Yusuke Horiuchi 1.2k 1.4× 942 1.2× 564 0.9× 339 0.6× 115 0.5× 91 1.7k
Vincent Agnus 321 0.4× 692 0.9× 327 0.5× 490 0.9× 52 0.2× 62 1.4k
Maria Vakalopoulou 501 0.6× 121 0.2× 432 0.7× 1.1k 2.0× 223 1.0× 30 1.5k
Omer F. Ahmad 205 0.2× 173 0.2× 331 0.5× 191 0.4× 106 0.5× 38 658
Tatsuya Ohnishi 313 0.4× 189 0.2× 287 0.5× 201 0.4× 110 0.5× 18 652

Countries citing papers authored by Fons van der Sommen

Since Specialization
Citations

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

Fields of papers citing papers by Fons van der Sommen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fons van der Sommen. 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 Fons van der Sommen. The network helps show where Fons van der Sommen may publish in the future.

Co-authorship network of co-authors of Fons van der Sommen

This figure shows the co-authorship network connecting the top 25 collaborators of Fons van der Sommen. A scholar is included among the top collaborators of Fons van der Sommen 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 Fons van der Sommen. Fons van der Sommen 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.
Fockens, Kiki, Britt B. S. L. Houwen, Manon van der Vlugt, et al.. (2025). Impact of standard enhancement settings of endoscopy systems on performance of endoscopic artificial intelligence systems. Endoscopy. 57(6). 602–610. 2 indexed citations
2.
Piek, Jurgen M.J., Fons van der Sommen, Max J. Lahaye, et al.. (2025). Artificial Intelligence and radiomics models for the diagnosis and prognosis of peritoneal metastases on imaging: a systematic review and meta-analysis. Computers in Biology and Medicine. 198(Pt B). 111188–111188.
3.
Duits, Lucas C., Roos E. Pouw, Bas L. Weusten, et al.. (2025). Evaluation of an improved computer-aided detection system for Barrett’s neoplasia in real-world imaging conditions. Endoscopy. 57(12). 1327–1337.
4.
Fockens, Kiki, et al.. (2025). Designing a Computer-Aided Detection system for Barrett ’s neoplasia: Insights in architectural choices, training strategies and inference approaches. Computer Methods and Programs in Biomedicine. 269. 108891–108891. 1 indexed citations
5.
Boers, Tim, Kiki Fockens, Joost van der Putten, et al.. (2025). Comparison of graphic user interfaces for computer-aided detection in Barrett’s neoplasia. Gastrointestinal Endoscopy. 102(5). 662–670.
6.
With, Peter H. N. de, et al.. (2025). AdverX-Ray: ensuring x-ray integrity through frequency-sensitive adversarial VAEs. TU/e Research Portal. 17–17.
7.
Fockens, Kiki, Tim Boers, Joost van der Putten, et al.. (2025). Challenges in Implementing Endoscopic Artificial Intelligence: The Impact of Real‐World Imaging Conditions on Barrett's Neoplasia Detection. United European Gastroenterology Journal. 13(6). 929–937. 2 indexed citations
8.
Jacobs, Igor, et al.. (2024). Robustness evaluation of CAD systems for lung nodule segmentation using clinically relevant image perturbations. TU/e Research Portal. 10. 76–76. 1 indexed citations
9.
Fockens, Kiki, et al.. (2024). Tu2011 IMAGE QUALITY CHALLENGES IN AI: IMPROVING ROBUSTNESS OF A COMPUTER AIDED DETECTION SYSTEM FOR BARRETT'S NEOPLASIA.. Gastroenterology. 166(5). S–1491. 2 indexed citations
10.
Kusters, Koen, Kiki Fockens, Tim Boers, et al.. (2024). DOMAIN-SPECIFIC DATA AUGMENTATION FOR ROBUST AI SYSTEMS IN ENDOSCOPY. Gastrointestinal Endoscopy. 99(6). AB27–AB28. 1 indexed citations
11.
12.
With, Peter H. N. de, et al.. (2024). Supervised Representation Learning Towards Generalizable Assembly State Recognition. IEEE Robotics and Automation Letters. 9(11). 9915–9922.
13.
14.
Fockens, Kiki, Joost van der Putten, Maarten R. Struyvenberg, et al.. (2024). Foundation models in gastrointestinal endoscopic AI: Impact of architecture, pre-training approach and data efficiency. Medical Image Analysis. 98. 103298–103298. 12 indexed citations
15.
16.
Putten, Joost van der, Xiaojuan Zhao, Arend Karrenbeld, et al.. (2023). Optical Biopsy of Dysplasia in Barrett’s Oesophagus Assisted by Artificial Intelligence. Cancers. 15(7). 1950–1950. 3 indexed citations
17.
With, Peter H. N. de, et al.. (2023). Probabilistic 3D segmentation for aleatoric uncertainty quantification in full 3D medical data. 31–31. 3 indexed citations
18.
Winkens, Björn, et al.. (2022). Artificial intelligence in (gastrointestinal) healthcare: patients’ and physicians’ perspectives. Scientific Reports. 12(1). 28 indexed citations
19.
Arribas, Julia, Giulio Antonelli, Leonardo Frazzoni, et al.. (2020). Standalone performance of artificial intelligence for upper GI neoplasia: a meta-analysis. Gut. 70(8). 1458–1468. 50 indexed citations
20.
Sommen, Fons van der, Himar Fabelo, Svitlana Zinger, et al.. (2020). Hyperspectral Imaging for Glioblastoma Surgery: Improving Tumor Identification Using a Deep Spectral-Spatial Approach. Sensors. 20(23). 6955–6955. 49 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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