M.H.F. Savenije

1.4k total citations
20 papers, 587 citations indexed

About

M.H.F. Savenije is a scholar working on Radiology, Nuclear Medicine and Imaging, Radiation and Biomedical Engineering. According to data from OpenAlex, M.H.F. Savenije has authored 20 papers receiving a total of 587 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Radiology, Nuclear Medicine and Imaging, 13 papers in Radiation and 8 papers in Biomedical Engineering. Recurrent topics in M.H.F. Savenije's work include Advanced Radiotherapy Techniques (13 papers), Medical Imaging Techniques and Applications (11 papers) and Radiomics and Machine Learning in Medical Imaging (5 papers). M.H.F. Savenije is often cited by papers focused on Advanced Radiotherapy Techniques (13 papers), Medical Imaging Techniques and Applications (11 papers) and Radiomics and Machine Learning in Medical Imaging (5 papers). M.H.F. Savenije collaborates with scholars based in Netherlands, Germany and Sweden. M.H.F. Savenije's co-authors include Cornelis A. T. van den Berg, Matteo Maspero, Enrica Seravalli, Peter R. Seevinck, Anna M. Dinkla, M.E.P. Philippens, Jochem R.N. van der Voort van Zyp, Joost J.C. Verhoeff, Jelmer M. Wolterink and Ivana Išgum and has published in prestigious journals such as International Journal of Radiation Oncology*Biology*Physics, Magnetic Resonance in Medicine and Physics in Medicine and Biology.

In The Last Decade

M.H.F. Savenije

17 papers receiving 575 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
M.H.F. Savenije Netherlands	10	459	329	179	132	90	20	587
Jianrong Dai China	11	434 0.9×	365 1.1×	146 0.8×	190 1.4×	62 0.7×	52	627
Jaehee Chun South Korea	12	323 0.7×	230 0.7×	100 0.6×	88 0.7×	60 0.7×	28	438
Joseph Harms United States	15	590 1.3×	468 1.4×	288 1.6×	262 2.0×	157 1.7×	54	916
Brent van der Heyden Netherlands	12	407 0.9×	306 0.9×	211 1.2×	219 1.7×	52 0.6×	33	591
Zohaib Iqbal United States	10	368 0.8×	261 0.8×	111 0.6×	123 0.9×	32 0.4×	26	518
Amirhossein Sanaat Switzerland	17	786 1.7×	174 0.5×	356 2.0×	91 0.7×	84 0.9×	57	928
Azadeh Akhavanallaf Switzerland	13	528 1.2×	143 0.4×	252 1.4×	108 0.8×	38 0.4×	29	626
Yesenia Gonzalez United States	10	327 0.7×	255 0.8×	133 0.7×	116 0.9×	69 0.8×	28	491
Matteo Maspero Netherlands	18	835 1.8×	632 1.9×	309 1.7×	249 1.9×	150 1.7×	45	1.1k
Brian Harrawood United States	16	519 1.1×	215 0.7×	346 1.9×	181 1.4×	143 1.6×	56	809

Countries citing papers authored by M.H.F. Savenije

Since Specialization

Citations

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

Fields of papers citing papers by M.H.F. Savenije

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M.H.F. Savenije. 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 M.H.F. Savenije. The network helps show where M.H.F. Savenije may publish in the future.

Co-authorship network of co-authors of M.H.F. Savenije

This figure shows the co-authorship network connecting the top 25 collaborators of M.H.F. Savenije. A scholar is included among the top collaborators of M.H.F. Savenije 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 M.H.F. Savenije. M.H.F. Savenije is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Thummerer, Adrian, Florian Kamp, M.H.F. Savenije, et al.. (2025). SynthRAD2025 Grand Challenge dataset: Generating synthetic CTs for radiotherapy from head to abdomen. Medical Physics. 52(7). e17981–e17981. 1 indexed citations

Doornaert, Patricia, M.H.F. Savenije, Ernst J. Smid, et al.. (2025). Comparable Performance Between Automatic and Manual Laryngeal and Hypopharyngeal Gross Tumor Volume Delineations Validated With Pathology. International Journal of Radiation Oncology*Biology*Physics. 122(1). 186–193.

Savenije, M.H.F., Mischa de Ridder, Matteo Maspero, et al.. (2024). Automatic segmentation for magnetic resonance imaging guided individual elective lymph node irradiation in head and neck cancer patients. Physics and Imaging in Radiation Oncology. 32. 100655–100655. 2 indexed citations

Berg, Ingeborg, M.H.F. Savenije, Harm H.E. van Melick, et al.. (2023). Deep learning for automated contouring of neurovascular structures on magnetic resonance imaging for prostate cancer patients. Physics and Imaging in Radiation Oncology. 26. 100453–100453. 8 indexed citations

Savenije, M.H.F., et al.. (2022). Clinical utility of convolutional neural networks for treatment planning in radiotherapy for spinal metastases. Physics and Imaging in Radiation Oncology. 21. 42–47. 9 indexed citations

Savenije, M.H.F., Matteo Maspero, G.G. Sikkes, et al.. (2020). Clinical implementation of MRI-based organs-at-risk auto-segmentation with convolutional networks for prostate radiotherapy. Radiation Oncology. 15(1). 104–104. 71 indexed citations

Maspero, Matteo, M.H.F. Savenije, Filipa Guerreiro, et al.. (2020). Deep learning-based synthetic CT generation for paediatric brain MR-only photon and proton radiotherapy. Radiotherapy and Oncology. 153. 197–204. 74 indexed citations

Maspero, Matteo, et al.. (2020). PD-0310: CBCT-to-CT synthesis with a single neural network for head-and-neck, lung and breast radiotherapy. Radiotherapy and Oncology. 152. S161–S161. 3 indexed citations

Berg, Cornelis A. T. van den, M.H.F. Savenije, H. Petra Kok, et al.. (2020). Deep learning‐based reconstruction of in vivo pelvis conductivity with a 3D patch‐based convolutional neural network trained on simulated MR data. Magnetic Resonance in Medicine. 84(5). 2772–2787. 30 indexed citations

10.

Maspero, Matteo, M.H.F. Savenije, A.N.T.J. Kotte, et al.. (2019). EP-2017 GANs covert CBCT to CT for head-neck, lung and breast: paired vs unpaired; single-site vs generic. Radiotherapy and Oncology. 133. S1105–S1106.

11.

Raaijmakers, Alexander, Alessandro Sbrizzi, Matteo Maspero, et al.. (2019). A deep learning method for image‐based subject‐specific local SAR assessment. Magnetic Resonance in Medicine. 83(2). 695–711. 33 indexed citations

12.

Kurz, Christopher, Matteo Maspero, M.H.F. Savenije, et al.. (2019). CBCT correction using a cycle-consistent generative adversarial network and unpaired training to enable photon and proton dose calculation. Physics in Medicine and Biology. 64(22). 225004–225004. 99 indexed citations

13.

Dinkla, Anna M., Mateusz C. Florkow, Matteo Maspero, et al.. (2019). Dosimetric evaluation of synthetic CT for head and neck radiotherapy generated by a patch‐based three‐dimensional convolutional neural network. Medical Physics. 46(9). 4095–4104. 78 indexed citations

14.

Eppenhof, Koen A. J., Matteo Maspero, M.H.F. Savenije, et al.. (2019). Fast contour propagation for MR‐guided prostate radiotherapy using convolutional neural networks. Medical Physics. 47(3). 1238–1248. 36 indexed citations

15.

Dinkla, Anna M., Jelmer M. Wolterink, Matteo Maspero, et al.. (2018). MR-Only Brain Radiation Therapy: Dosimetric Evaluation of Synthetic CTs Generated by a Dilated Convolutional Neural Network. International Journal of Radiation Oncology*Biology*Physics. 102(4). 801–812. 110 indexed citations

16.

Savenije, M.H.F., Matteo Maspero, Anna M. Dinkla, Peter R. Seevinck, & Cornelis A. T. van den Berg. (2018). OC-0294: MR-based synthetic CT with conditional Generative Adversarial Network for prostate RT planning. Radiotherapy and Oncology. 127. S151–S152. 1 indexed citations

17.

Dinkla, Anna M., Jelmer M. Wolterink, Matteo Maspero, et al.. (2018). OC-0293: Dosimetric evaluation of deep learning based synthetic-CT generation for MR-only brain radiotherapy. Radiotherapy and Oncology. 127. S151–S151.

18.

Kurz, Christopher, David C. Hansen, M.H.F. Savenije, et al.. (2018). [OA127] Cone-beam CT intensity correction for adaptive radiotherapy of the prostate using deep learning. Physica Medica. 52. 48–48. 5 indexed citations

19.

Maspero, Matteo, M.H.F. Savenije, Anna M. Dinkla, et al.. (2018). Fast synthetic CT generation with deep learning for general pelvis MR-only Radiotherapy.. 5 indexed citations

20.

Barkema, G. T., et al.. (1992). A Fast Partitioning Algorithm and a Comparison of Binary Feedforward Neural Networks. Europhysics Letters (EPL). 18(6). 555–559. 22 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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