Frederic Madesta

1.0k total citations
19 papers, 563 citations indexed

About

Frederic Madesta is a scholar working on Radiology, Nuclear Medicine and Imaging, Radiation and Biomedical Engineering. According to data from OpenAlex, Frederic Madesta has authored 19 papers receiving a total of 563 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Radiology, Nuclear Medicine and Imaging, 13 papers in Radiation and 8 papers in Biomedical Engineering. Recurrent topics in Frederic Madesta's work include Medical Imaging Techniques and Applications (14 papers), Advanced Radiotherapy Techniques (13 papers) and Advanced X-ray and CT Imaging (7 papers). Frederic Madesta is often cited by papers focused on Medical Imaging Techniques and Applications (14 papers), Advanced Radiotherapy Techniques (13 papers) and Advanced X-ray and CT Imaging (7 papers). Frederic Madesta collaborates with scholars based in Germany, United States and Canada. Frederic Madesta's co-authors include René Werner, Tobias Gauer, Thilo Sentker, Helge Kniep, Rüdiger Schmitz, Gerhard Schön, Jens Fiehler, Michael Schönfeld, Susanne Gellißen and Uta Hanning and has published in prestigious journals such as Radiology, International Journal of Radiation Oncology*Biology*Physics and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Frederic Madesta

18 papers receiving 557 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Frederic Madesta Germany 10 368 169 140 131 130 19 563
Changjuan Tao China 12 321 0.9× 66 0.4× 93 0.7× 174 1.3× 157 1.2× 29 703
Siri Willems Belgium 11 342 0.9× 158 0.9× 107 0.8× 185 1.4× 49 0.4× 14 616
Elisa Scalco Italy 15 577 1.6× 84 0.5× 165 1.2× 136 1.0× 79 0.6× 50 778
M Jermoumi United States 4 586 1.6× 115 0.7× 228 1.6× 47 0.4× 99 0.8× 9 668
Kanabu Nawa Japan 9 385 1.0× 58 0.3× 137 1.0× 232 1.8× 31 0.2× 23 495
Baher Elgohari United States 16 323 0.9× 71 0.4× 101 0.7× 122 0.9× 109 0.8× 33 616
Qingtao Qiu China 16 495 1.3× 59 0.3× 118 0.8× 39 0.3× 134 1.0× 51 614
H. Geng United States 10 288 0.8× 55 0.3× 83 0.6× 255 1.9× 47 0.4× 26 509
Lars Bornemann Germany 11 608 1.7× 121 0.7× 99 0.7× 72 0.5× 66 0.5× 22 800
Khaled Bousabarah United States 11 312 0.8× 48 0.3× 73 0.5× 40 0.3× 93 0.7× 29 492

Countries citing papers authored by Frederic Madesta

Since Specialization
Citations

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

Fields of papers citing papers by Frederic Madesta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Frederic Madesta

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

All Works

19 of 19 papers shown
1.
Hurkmans, Coen, Jean‐Emmanuel Bibault, Kristy K. Brock, et al.. (2024). A joint ESTRO and AAPM guideline for development, clinical validation and reporting of artificial intelligence models in radiation therapy. Radiotherapy and Oncology. 197. 110345–110345. 29 indexed citations
2.
3.
Madesta, Frederic, et al.. (2024). Benchmarking machine learning‐based real‐time respiratory signal predictors in 4D SBRT. Medical Physics. 51(5). 3173–3183. 2 indexed citations
4.
Werner, René, Frederic Madesta, Thilo Sentker, et al.. (2023). Clinical application of breathing-adapted 4D CT: image quality comparison to conventional 4D CT. Strahlentherapie und Onkologie. 199(7). 686–691. 9 indexed citations
5.
Madesta, Frederic, Matthias Bechstein, Lukas Meyer, et al.. (2023). Discordant and Converting Receptor Expressions in Brain Metastases from Breast Cancer: MRI-Based Non-Invasive Receptor Status Tracking. Cancers. 15(11). 2880–2880. 2 indexed citations
6.
Madesta, Frederic, Lennart Well, Isabel Molwitz, et al.. (2022). Evaluation of magnetic resonance imaging-based radiomics characteristics for differentiation of benign and malignant peripheral nerve sheath tumors in neurofibromatosis type 1. Neuro-Oncology. 24(10). 1790–1798. 14 indexed citations
7.
Schmitz, Rüdiger, Frederic Madesta, Jenny Krause, et al.. (2021). Multi-scale fully convolutional neural networks for histopathology image segmentation: From nuclear aberrations to the global tissue architecture. Medical Image Analysis. 70. 101996–101996. 70 indexed citations
8.
Madesta, Frederic, Rüdiger Schmitz, Thomas Rösch, & René Werner. (2021). Abstract: Widening the Focus - Biomedical Image Segmentation Challenges and the Underestimated Role of Patch Sampling and Inference Strategies.. 253. 1 indexed citations
9.
Werner, René, Thilo Sentker, Frederic Madesta, et al.. (2020). Comparison of intelligent 4D CT sequence scanning and conventional spiral 4D CT: a first comprehensive phantom study. Physics in Medicine and Biology. 66(1). 15004–15004. 17 indexed citations
10.
Sentker, Thilo, Ann‐Kathrin Ozga, Cordula Petersen, et al.. (2020). 4D CT image artifacts affect local control in SBRT of lung and liver metastases. Radiotherapy and Oncology. 148. 229–234. 33 indexed citations
11.
Madesta, Frederic, Thilo Sentker, Tobias Gauer, & René Werner. (2020). Self‐contained deep learning‐based boosting of 4D cone‐beam CT reconstruction. Medical Physics. 47(11). 5619–5631. 27 indexed citations
12.
13.
Werner, René, Thilo Sentker, Frederic Madesta, Tobias Gauer, & Christian Hofmann. (2019). Intelligent 4D CT sequence scanning (i4DCT): Concept and performance evaluation. Medical Physics. 46(8). 3462–3474. 27 indexed citations
14.
Sentker, Thilo, Frederic Madesta, & René Werner. (2019). Patient-specific 4D Monte Carlo dose accumulation using correspondence-model-based motion prediction. 8–8.
15.
Madesta, Frederic, Tobias Gauer, Thilo Sentker, & René Werner. (2019). Self-consistent deep learning-based boosting of 4D cone-beam computed tomography reconstruction. 1–1. 5 indexed citations
16.
Gessert, Nils, Thilo Sentker, Frederic Madesta, et al.. (2019). Skin Lesion Classification Using CNNs With Patch-Based Attention and Diagnosis-Guided Loss Weighting. IEEE Transactions on Biomedical Engineering. 67(2). 495–503. 125 indexed citations
17.
Kniep, Helge, Frederic Madesta, Tanja Schneider, et al.. (2018). Radiomics of Brain MRI: Utility in Prediction of Metastatic Tumor Type. Radiology. 290(2). 479–487. 176 indexed citations
18.
Werner, René, et al.. (2018). Technical considerations for automated low-pitch spiral 4D CT scanning protocol selection. 142–142. 3 indexed citations
19.
Werner, René, et al.. (2018). Intelligent 4D CT Sequence Scanning (i4DCT). International Journal of Radiation Oncology*Biology*Physics. 102(3). S5–S5. 1 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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