Peter M. A. van Ooijen

13.8k citations

257 papers · 6.0k indexed · 2 hit papers · h-index 41

Health Informatics top 0.2%
Radiology, Nuclear Medicine and Imaging top 0.2%
- Cardiac Imaging and Diagnostics 66
- Radiomics and Machine Learning in Medical Imaging 65
- Advanced MRI Techniques and Applications 37
- Radiation Dose and Imaging 27
- Medical Imaging Techniques and Applications 27
Pulmonary and Respiratory Medicine top 1%
- Lung Cancer Diagnosis and Treatment 44
Internal Medicine top 5%
Biomedical Engineering top 2%
- Advanced X-ray and CT Imaging 54
- Medical Imaging and Analysis 17

Co-authors: Matthijs Oudkerk Rozemarijn Vliegenthart Robert‐Jan van Geuns Benno J. Rensing Geertruida H. de Bock Marjolein A. Heuvelmans Harry J.M. Groen Koen Nieman
Cited by: Health Informatics Radiology, Nuclear Medicine and Imaging Pulmonary and Respiratory Medicine
Journals: The Lancet (2 papers)Circulation (3 papers)SHILAP Revista de lepidopterología (1 paper)
Partner nations: Netherlands United States China

In The Last Decade

Peter M. A. van Ooijen

244 papers receiving 5.9k citations

Hit Papers

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Peers

Countries citing papers authored by Peter M. A. van Ooijen

Since Specialization

Citations

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

Fields of papers citing papers by Peter M. A. van Ooijen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter M. A. van Ooijen. 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 Peter M. A. van Ooijen. The network helps show where Peter M. A. van Ooijen may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Peter M. A. van Ooijen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Peter M. A. van Ooijen Line = papers co-authored together Peter M. A. van Ooijen links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

#	Work
1	Uncertainty-aware deep learning for segmentation of primary tumor and pathologic lymph nodes in oropharyngeal cancer: Insights from a multi-center cohort Computerized Medical Imaging and Graphics ·Alessia de Biase,Nanna M. Sijtsema,Lisanne V. van Dijk,Roel J.H.M. Steenbakkers,Johannes A. Langendijk,Peter M. A. van Ooijen	2025	1
2	MRI-Based Head and Neck Tumor Segmentation Using nnU-Net with 15-Fold Cross-Validation Ensemble Lecture notes in computer science ·Frank N. Mol,Luuk Van der Hoek,Baoqiang Ma,B.C Nagam,Nanna M. Sijtsema,Lisanne V. van Dijk,Kerstin Bunte,Rifka Vlijm,Peter M. A. van Ooijen	2025	0
3	Automatic two-dimensional & three-dimensional video analysis with deep learning for movement disorders: A systematic review Artificial Intelligence in Medicine ·Wei Tang,Peter M. A. van Ooijen,Deborah A. Sival,Natasha M. Maurits	2024	5
4	A framework to integrate artificial intelligence training into radiology residency programs: preparing the future radiologist Insights into Imaging ·Maria Jorina van Kooten,Can Ozan Tan,Elfi Inez Saïda Hofmeijer,Peter M. A. van Ooijen,Walter Noordzij,Maria J. Lamers,Thomas C. Kwee,Rozemarijn Vliegenthart,Derya Yakar	2024	17
5	Clinical adoption of deep learning target auto-segmentation for radiation therapy: challenges, clinical risks, and mitigation strategies TU/e Research Portal ·Alessia de Biase,Nanna M. Sijtsema,Tomas Janssen,Coen Hurkmans,Charlotte L. Brouwer,Peter M. A. van Ooijen	2024	5
6	Exploring Adversarial Attacks in Federated Learning for Medical Imaging IEEE Transactions on Industrial Informatics ·Erfan Darzi,Florian Dubost,Nanna M. Sijtsema,Peter M. A. van Ooijen	2024	12
7	Localization of contrast-enhanced breast lesions in ultrafast screening MRI using deep convolutional neural networks European Radiology ·Xueping Jing,Monique D. Dorrius,Sunyi Zheng,Mirjam Wielema,Matthijs Oudkerk,Paul E. Sijens,Peter M. A. van Ooijen	2023	7
8	CT‐based deep multi‐label learning prediction model for outcome in patients with oropharyngeal squamous cell carcinoma Medical Physics ·Baoqiang Ma,Jiapan Guo,Tian‐Tian Zhai,A. van der Schaaf,R.J.H.M. Steenbakkers,Lisanne V. van Dijk,Stefan Both,Johannes A. Langendijk,Weichuan Zhang,Bingjiang Qiu,Peter M. A. van Ooijen,Nanna M. Sijtsema	2023	8
9	Comparison of computed tomography image features extracted by radiomics, self-supervised learning and end-to-end deep learning for outcome prediction of oropharyngeal cancer Physics and Imaging in Radiation Oncology ·Baoqiang Ma,Jiapan Guo,Hung Chu,Lisanne V. van Dijk,Peter M. A. van Ooijen,Johannes A. Langendijk,Stefan Both,Nanna M. Sijtsema	2023	7
10	The U-Net Family for Epicardial Adipose Tissue Segmentation and Quantification in Low-Dose CT SHILAP Revista de lepidopterología ·Lu Liu,Runlei Ma,Peter M. A. van Ooijen,Matthijs Oudkerk,Rozemarijn Vliegenthart,Raymond Veldhuis,Christoph Brüne	2023	3
11	Deep learning-based outcome prediction using PET/CT and automatically predicted probability maps of primary tumor in patients with oropharyngeal cancer Computer Methods and Programs in Biomedicine ·Alessia de Biase,Baoqiang Ma,Jiapan Guo,Lisanne V. van Dijk,Johannes A. Langendijk,Stefan Both,Peter M. A. van Ooijen,Nanna M. Sijtsema	2023	10
12	Survival prediction for stage I-IIIA non-small cell lung cancer using deep learning Radiotherapy and Oncology ·Sunyi Zheng,Jiapan Guo,Johannes A. Langendijk,Stefan Both,Raymond Veldhuis,Matthijs Oudkerk,Peter M. A. van Ooijen,Robin Wijsman,Nanna M. Sijtsema	2023	22
13	Reproducibility of radiomics quality score: an intra- and inter-rater reliability study European Radiology ·Tugba Akinci D’Antonoli,Armando Ugo Cavallo,Federica Vernuccio,Arnaldo Stanzione,Michail E. Klontzas,Roberto Cannella,Lorenzo Ugga,Agah Baran,Salvatore Claudio Fanni,EA Petrash,Ilaria Ambrosini,L.A. Cappellini,Peter M. A. van Ooijen,Elmar Kotter,Daniel Pinto dos Santos,Renato Cuocolo,(unknown)	2023	34
14	Deep learning aided oropharyngeal cancer segmentation with adaptive thresholding for predicted tumor probability in FDG PET and CT images Physics in Medicine and Biology ·Alessia de Biase,Nanna M. Sijtsema,Lisanne V. van Dijk,Johannes A. Langendijk,Peter M. A. van Ooijen	2023	17
15	Pre-screening to guide coronary artery calcium scoring for early identification of high-risk individuals in the general population European Heart Journal - Cardiovascular Imaging ·Daan Ties,M. Yldau van der Ende,Gabija Pundziūtė,Yvonne T. van der Schouw,Michiel L. Bots,Congying Xia,Peter M. A. van Ooijen,Gert Jan Pelgrim,Rozemarijn Vliegenthart,Pim van der Harst	2022	7
16	Federated Learning in Medical Imaging: Part I: Toward Multicentral Health Care Ecosystems Journal of the American College of Radiology ·Erfan Darzidehkalani,Mohammad Ghasemi-Rad,Peter M. A. van Ooijen	2022	44
17	Robust and Accurate Mandible Segmentation on Dental CBCT Scans Affected by Metal Artifacts Using a Prior Shape Model Journal of Personalized Medicine ·Bingjiang Qiu,Hylke van der Wel,Joep Kraeima,Haye H. Glas,Jiapan Guo,Ronald Borra,Max J. H. Witjes,Peter M. A. van Ooijen	2021	17
18	Automatic segmentation of the mandible from computed tomography scans for 3D virtual surgical planning using the convolutional neural network Physics in Medicine and Biology ·Bingjiang Qiu,Jiapan Guo,Joep Kraeima,Haye H. Glas,Ronald Borra,Max J. H. Witjes,Peter M. A. van Ooijen	2019	46
19	3D segmentation of mandible from multisectional CT scans by convolutional neural networks Data Archiving and Networked Services (DANS) ·Bingjiang Qiu,Jiapan Guo,Joep Kraeima,Ronald Borra,Max J. H. Witjes,Peter M. A. van Ooijen	2018	3
20	Comparison of contrast-enhanced MRA and DSA for the diagnosis of pulmonary embolism: results of a prospective study in 141 patients with an abnormal perfusion lung scan European Radiology ·Matthijs Oudkerk,Edwin J.R. van Beek,P. Wielopolski,Peter M. A. van Ooijen,Elise M. J. Brouwers-Kuyper,Alphons H.H. Bongaerts,Arie Berghout	2002	1

About Peter M. A. van Ooijen

Peter M. A. van Ooijen is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 257 papers that have together received 6.0k indexed citations. Recurring topics across this work include Cardiac Imaging and Diagnostics (66 papers), Radiomics and Machine Learning in Medical Imaging (65 papers), Advanced X-ray and CT Imaging (54 papers), Lung Cancer Diagnosis and Treatment (44 papers), Advanced MRI Techniques and Applications (37 papers), Radiation Dose and Imaging (27 papers), Medical Imaging Techniques and Applications (27 papers) and Medical Imaging and Analysis (17 papers). The work is most often cited by research in Health Informatics (298 citations), Radiology, Nuclear Medicine and Imaging (3.5k citations) and Pulmonary and Respiratory Medicine (2.0k citations). Peter M. A. van Ooijen has collaborated with scholars based in Netherlands, United States and China. Frequent co-authors include Matthijs Oudkerk, Rozemarijn Vliegenthart, Robert‐Jan van Geuns, Benno J. Rensing, Geertruida H. de Bock, Marjolein A. Heuvelmans, Harry J.M. Groen, Koen Nieman, Pim A. de Jong and P. J. de Feyter. Their work appears in journals such as The Lancet, Circulation and SHILAP Revista de lepidopterología.

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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