Jens Maus

512 total citations
21 papers, 372 citations indexed

About

Jens Maus is a scholar working on Radiology, Nuclear Medicine and Imaging, Radiation and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Jens Maus has authored 21 papers receiving a total of 372 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Radiology, Nuclear Medicine and Imaging, 6 papers in Radiation and 4 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Jens Maus's work include Medical Imaging Techniques and Applications (17 papers), Radiomics and Machine Learning in Medical Imaging (11 papers) and Advanced MRI Techniques and Applications (8 papers). Jens Maus is often cited by papers focused on Medical Imaging Techniques and Applications (17 papers), Radiomics and Machine Learning in Medical Imaging (11 papers) and Advanced MRI Techniques and Applications (8 papers). Jens Maus collaborates with scholars based in Germany, Belgium and Canada. Jens Maus's co-authors include Jörg van den Hoff, Georg Schramm, Bettina Beuthien‐Baumann, Frank Hofheinz, Jan Petr, Alexandr Lougovski, Liane Oehme, Ivan Platzek, Jörg Kotzerke and Michael Laniado and has published in prestigious journals such as Physics in Medicine and Biology, Medical Physics and Radiotherapy and Oncology.

In The Last Decade

Jens Maus

19 papers receiving 364 citations

Peers

Jens Maus

RNMI

PRM

GENET

SURGE

Russell Frood United Kingdom

Yukihiko Ozawa Japan

Patsuree Cheebsumon Netherlands

Emma D’Ippolito Italy

Andrés Kohan Canada

Thomas Koopman Netherlands

N Hayashi Japan

J.L. Vercher-Conejero Spain

Johannes Roesch Germany

Dasantha Jayamanne Australia

Russell Frood United Kingdom

Jens Maus

252 ×0.9

RNMI

134 ×1.2

PRM

28 ×0.5

GENET

63 ×1.4

SURGE

41 ×1.1

Citations per year, relative to Jens Maus Jens Maus (= 1×) peers Russell Frood

Countries citing papers authored by Jens Maus

Since Specialization

Citations

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

Fields of papers citing papers by Jens Maus

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jens Maus

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

All Works

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20 of 20 papers shown

Maus, Jens, Frank Hofheinz, Jan Petr, et al.. (2024). Deep learning based bilateral filtering for edge-preserving denoising of respiratory-gated PET. EJNMMI Physics. 11(1). 58–58. 5 indexed citations

Hofheinz, Frank, et al.. (2023). An unsupervised deep learning framework for respiratory motion correction in PET. Nuklearmedizin - NuclearMedicine. 62(2). 116–116.

Zschaeck, Sebastian, Jens Maus, Christian Furth, et al.. (2023). A convolutional neural network with self-attention for fully automated metabolic tumor volume delineation of head and neck cancer in $$[^{18}$$F]FDG PET/CT. European Journal of Nuclear Medicine and Molecular Imaging. 50(9). 2751–2766. 6 indexed citations

Hofheinz, Frank, Jens Maus, Yimin Li, et al.. (2020). A convolutional neural network for fully automated blood SUV determination to facilitate SUR computation in oncological FDG-PET. European Journal of Nuclear Medicine and Molecular Imaging. 48(4). 995–1004. 5 indexed citations

Hofheinz, Frank, Jens Maus, Sebastian Zschaeck, et al.. (2019). Interobserver variability of image-derived arterial blood SUV in whole-body FDG PET. EJNMMI Research. 9(1). 23–23. 4 indexed citations

Maus, Jens, et al.. (2019). Time efficient scatter correction for time-of-flight PET: the immediate scatter approximation. Physics in Medicine and Biology. 64(7). 75005–75005. 2 indexed citations

Petr, Jan, Ivan Platzek, Frank Hofheinz, et al.. (2018). Photon vs. proton radiochemotherapy: Effects on brain tissue volume and perfusion. Radiotherapy and Oncology. 128(1). 121–127. 48 indexed citations

Platzek, Ivan, Bettina Beuthien‐Baumann, Georg Schramm, et al.. (2016). FDG PET/MR in initial staging of sarcoma: Initial experience and comparison with conventional imaging. Clinical Imaging. 42. 126–132. 18 indexed citations

Lougovski, Alexandr, Frank Hofheinz, Jens Maus, Georg Schramm, & Jörg van den Hoff. (2015). On the relation between Kaiser–Bessel blob and tube of response based modelling of the system matrix in iterative PET image reconstruction. Physics in Medicine and Biology. 60(10). 4209–4224. 4 indexed citations

10.

Schramm, Georg, Jens Maus, Frank Hofheinz, et al.. (2015). Correction of quantification errors in pelvic and spinal lesions caused by ignoring higher photon attenuation of bone in [¹⁸F]NaF PET/MR. Medical Physics. 42(11). 6468–6476. 8 indexed citations

11.

Petr, Jan, Ivan Platzek, Annekatrin Seidlitz, et al.. (2015). Early and late effects of radiochemotherapy on cerebral blood flow in glioblastoma patients measured with non-invasive perfusion MRI. Radiotherapy and Oncology. 118(1). 24–28. 29 indexed citations

12.

Maus, Jens, Georg Schramm, Frank Hofheinz, et al.. (2015). Evaluation of in vivo quantification accuracy of the Ingenuity‐TF PET/MR. Medical Physics. 42(10). 5773–5781. 4 indexed citations

13.

Platzek, Ivan, Bettina Beuthien‐Baumann, Matthias Schneider, et al.. (2014). FDG PET/MR for lymph node staging in head and neck cancer. European Journal of Radiology. 83(7). 1163–1168. 45 indexed citations

14.

Platzek, Ivan, Bettina Beuthien‐Baumann, Jens Maus, et al.. (2014). FDG PET/MR for the Assessment of Lymph Node Involvement in Lymphoma. Academic Radiology. 21(10). 1314–1319. 20 indexed citations

15.

Schramm, Georg, Jens Maus, Frank Hofheinz, et al.. (2014). Evaluation and automatic correction of metal-implant-induced artifacts in MR-based attenuation correction in whole-body PET/MR imaging. Physics in Medicine and Biology. 59(11). 2713–2726. 20 indexed citations

16.

Lougovski, Alexandr, et al.. (2014). A volume of intersection approach for on-the-fly system matrix calculation in 3D PET image reconstruction. Physics in Medicine and Biology. 59(3). 561–577. 15 indexed citations

17.

Hofheinz, Frank, Georg Schramm, Liane Oehme, et al.. (2014). Evaluation of PET quantification accuracy in vivo. Nuklearmedizin - NuclearMedicine. 53(3). 67–77. 5 indexed citations

18.

Hoff, Jörg van den, Alexandr Lougovski, Georg Schramm, et al.. (2014). Correction of scan time dependence of standard uptake values in oncological PET. EJNMMI Research. 4(1). 18–18. 40 indexed citations

19.

Lougovski, Alexandr, et al.. (2014). Preliminary evaluation of the MLAA algorithm with the Philips Ingenuity PET/MR. EJNMMI Physics. 1(S1). A33–A33. 3 indexed citations

20.

Hoff, Jörg van den, Liane Oehme, Georg Schramm, et al.. (2013). The PET-derived tumor-to-blood standard uptake ratio (SUR) is superior to tumor SUV as a surrogate parameter of the metabolic rate of FDG. EJNMMI Research. 3(1). 77–77. 91 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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