Judith Herrmann

1.4k total citations
60 papers, 966 citations indexed

About

Judith Herrmann is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Biomedical Engineering. According to data from OpenAlex, Judith Herrmann has authored 60 papers receiving a total of 966 indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Radiology, Nuclear Medicine and Imaging, 12 papers in Pulmonary and Respiratory Medicine and 7 papers in Biomedical Engineering. Recurrent topics in Judith Herrmann's work include Advanced MRI Techniques and Applications (27 papers), MRI in cancer diagnosis (21 papers) and Medical Imaging Techniques and Applications (11 papers). Judith Herrmann is often cited by papers focused on Advanced MRI Techniques and Applications (27 papers), MRI in cancer diagnosis (21 papers) and Medical Imaging Techniques and Applications (11 papers). Judith Herrmann collaborates with scholars based in Germany, United States and Switzerland. Judith Herrmann's co-authors include Sebastian Gassenmaier, Saif Afat, Dominik Nickel, Ahmed E. Othman, Haidara Almansour, Mahmoud Mostapha, Konstantin Nikolaou, E. C. Herrmann, Gregor Koerzdoerfer and Simon Arberet and has published in prestigious journals such as Radiology, Annals of the New York Academy of Sciences and The Journal of Infectious Diseases.

In The Last Decade

Judith Herrmann

56 papers receiving 951 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Judith Herrmann Germany 20 735 179 170 78 74 60 966
Azadeh Tabari United States 14 467 0.6× 302 1.7× 100 0.6× 94 1.2× 22 0.3× 54 680
Sha Zhao United Kingdom 12 625 0.9× 127 0.7× 61 0.4× 83 1.1× 22 0.3× 34 902
Horst Lenzen Germany 13 691 0.9× 222 1.2× 695 4.1× 79 1.0× 62 0.8× 22 1.1k
Thomas Elgeti Germany 19 656 0.9× 423 2.4× 187 1.1× 192 2.5× 39 0.5× 77 1.1k
Harsh Agarwal United States 16 395 0.5× 94 0.5× 345 2.0× 81 1.0× 23 0.3× 46 795
Nestor L. Müller Canada 6 328 0.4× 66 0.4× 496 2.9× 91 1.2× 54 0.7× 6 679
Verena Carola Obmann Switzerland 15 387 0.5× 154 0.9× 196 1.2× 67 0.9× 14 0.2× 51 612
Jesús C. Pueyo Spain 15 320 0.4× 106 0.6× 694 4.1× 102 1.3× 27 0.4× 38 1.2k
Hansjörg Rempp Germany 18 327 0.4× 252 1.4× 145 0.9× 102 1.3× 23 0.3× 33 737

Countries citing papers authored by Judith Herrmann

Since Specialization
Citations

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

Fields of papers citing papers by Judith Herrmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Judith Herrmann

This figure shows the co-authorship network connecting the top 25 collaborators of Judith Herrmann. A scholar is included among the top collaborators of Judith Herrmann 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 Judith Herrmann. Judith Herrmann 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.
2.
Streich, Sebastian, Ruth Ladurner, Sebastian Gassenmaier, et al.. (2025). Evaluation of a Deep Learning Denoising Algorithm for Dose Reduction in Whole-Body Photon-Counting CT Imaging: A Cadaveric Study. Academic Radiology. 32(6). 3519–3531.
3.
Herrmann, Judith, You‐Shan Feng, Sebastian Gassenmaier, et al.. (2024). Fast 5-minute shoulder MRI protocol with accelerated TSE-sequences and deep learning image reconstruction for the assessment of shoulder pain at 1.5 and 3 Tesla. European Journal of Radiology Open. 12. 100557–100557. 3 indexed citations
4.
Herrmann, Judith, et al.. (2024). Prospective Deployment of Deep Learning Reconstruction Facilitates Highly Accelerated Upper Abdominal MRI. Academic Radiology. 31(12). 4965–4973. 7 indexed citations
5.
Grunz, Jan‐Peter, Henner Huflage, Philipp Gruschwitz, et al.. (2023). Ultra-high resolution photon-counting CT with tin prefiltration for bone-metal interface visualization. European Journal of Radiology. 170. 111209–111209. 9 indexed citations
6.
Herrmann, Judith, Haidara Almansour, Dominik Nickel, et al.. (2023). Application of deep learning-based super-resolution to T1-weighted postcontrast gradient echo imaging of the chest. La radiologia medica. 128(2). 184–190. 11 indexed citations
7.
Ursprung, Stephan, Judith Herrmann, Elisabeth Weiland, et al.. (2023). Accelerated diffusion-weighted imaging of the prostate using deep learning image reconstruction: A retrospective comparison with standard diffusion-weighted imaging. European Journal of Radiology. 165. 110953–110953. 21 indexed citations
8.
Gassenmaier, Sebastian, Dominik Nickel, Elisabeth Weiland, et al.. (2023). Thin-Slice Prostate MRI Enabled by Deep Learning Image Reconstruction. Cancers. 15(3). 578–578. 21 indexed citations
9.
Herrmann, Judith, Saif Afat, Sebastian Gassenmaier, et al.. (2023). Image Quality and Diagnostic Performance of Accelerated 2D Hip MRI with Deep Learning Reconstruction Based on a Deep Iterative Hierarchical Network. Diagnostics. 13(20). 3241–3241. 2 indexed citations
10.
Herrmann, Judith, et al.. (2023). Self-learning Agents for Recommerce Markets. Business & Information Systems Engineering. 66(4). 441–463. 5 indexed citations
11.
Herrmann, Judith, Thomas Benkert, Andreas Brendlin, et al.. (2023). Shortening Acquisition Time and Improving Image Quality for Pelvic MRI Using Deep Learning Reconstruction for Diffusion-Weighted Imaging at 1.5 T. Academic Radiology. 31(3). 921–928. 5 indexed citations
12.
Ursprung, Stephan, et al.. (2023). Die multiparametrische MRT der Prostata: Anforderungen und Grundlagen der Befundung. PubMed. 62(5). 449–458. 1 indexed citations
13.
Artzner, Christoph, Malte N. Bongers, Sebastian Faby, et al.. (2022). Assessing the Accuracy of an Artificial Intelligence-Based Segmentation Algorithm for the Thoracic Aorta in Computed Tomography Applications. Diagnostics. 12(8). 1790–1790. 11 indexed citations
14.
Afat, Saif, Judith Herrmann, Haidara Almansour, et al.. (2022). Acquisition time reduction of diffusion-weighted liver imaging using deep learning image reconstruction. Diagnostic and Interventional Imaging. 104(4). 178–184. 30 indexed citations
15.
Herrmann, Judith, Dominik Nickel, Simon Arberet, et al.. (2022). Comprehensive Clinical Evaluation of a Deep Learning-Accelerated, Single-Breath-Hold Abdominal HASTE at 1.5 T and 3 T. Academic Radiology. 30(1). 93–102. 11 indexed citations
16.
Herrmann, Judith, Sascha Kaufmann, Steffen Rausch, et al.. (2022). Multiparametrische MRT der Prostata. Der Urologe. 61(4). 428–440. 4 indexed citations
17.
18.
Herrmann, Judith, Sebastian Gassenmaier, Dominik Nickel, et al.. (2022). Feasibility of an accelerated 2D-multi-contrast knee MRI protocol using deep-learning image reconstruction: a prospective intraindividual comparison with a standard MRI protocol. European Radiology. 32(9). 6215–6229. 32 indexed citations
19.
20.
Herrmann, Judith. (2012). A critical analysis of the transitional justice measures incorporated by Rwandan gacaca and their effectiveness. ResearchOnline at James Cook University (James Cook University). 19. 90. 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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