Bernhard Preim

7.7k total citations
341 papers, 4.5k citations indexed

About

Bernhard Preim is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Computational Mechanics. According to data from OpenAlex, Bernhard Preim has authored 341 papers receiving a total of 4.5k indexed citations (citations by other indexed papers that have themselves been cited), including 150 papers in Computer Vision and Pattern Recognition, 86 papers in Computer Graphics and Computer-Aided Design and 59 papers in Computational Mechanics. Recurrent topics in Bernhard Preim's work include Computer Graphics and Visualization Techniques (85 papers), 3D Shape Modeling and Analysis (57 papers) and Intracranial Aneurysms: Treatment and Complications (51 papers). Bernhard Preim is often cited by papers focused on Computer Graphics and Visualization Techniques (85 papers), 3D Shape Modeling and Analysis (57 papers) and Intracranial Aneurysms: Treatment and Complications (51 papers). Bernhard Preim collaborates with scholars based in Germany, Austria and United States. Bernhard Preim's co-authors include Kai Lawonn, H.-O. Peitgen, Steffen Oeltze, Dirk Selle, Patrick Saalfeld, Andrea Schenk, Oliver Beuing, Rocco Gasteiger, Timo Ropinski and Christian Tietjen and has published in prestigious journals such as SHILAP Revista de lepidopterología, NeuroImage and Scientific Reports.

In The Last Decade

Bernhard Preim

321 papers receiving 4.3k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Bernhard Preim Germany	36	2.3k	1.1k	873	720	639	341	4.5k
Adrian Hilton United Kingdom	42	4.7k 2.1×	667 0.6×	297 0.3×	1.1k 1.6×	835 1.3×	325	8.4k
Yizhou Yu China	51	6.2k 2.7×	830 0.8×	1.5k 1.8×	727 1.0×	464 0.7×	221	9.5k
Ghassan Hamarneh Canada	39	2.7k 1.2×	271 0.3×	1.9k 2.2×	552 0.8×	1.1k 1.7×	252	6.7k
Dimitris Metaxas United States	40	3.3k 1.4×	669 0.6×	1.5k 1.7×	1.2k 1.6×	906 1.4×	181	6.0k
Ioannis A. Kakadiaris United States	41	3.6k 1.6×	116 0.1×	985 1.1×	416 0.6×	870 1.4×	266	6.1k
Anna Vilanova Netherlands	28	870 0.4×	327 0.3×	930 1.1×	178 0.2×	217 0.3×	132	2.8k
Benoı̂t Macq Belgium	35	3.0k 1.3×	189 0.2×	880 1.0×	227 0.3×	678 1.1×	298	5.4k
Hans-Peter Meinzer Germany	32	1.3k 0.6×	119 0.1×	1.1k 1.3×	267 0.4×	1.3k 2.0×	132	4.1k
Horst K. Hahn Germany	31	796 0.3×	151 0.1×	1.2k 1.4×	137 0.2×	427 0.7×	182	3.0k
Punam K. Saha United States	41	2.3k 1.0×	216 0.2×	1.8k 2.0×	192 0.3×	886 1.4×	207	5.8k

Countries citing papers authored by Bernhard Preim

Since Specialization

Citations

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

Fields of papers citing papers by Bernhard Preim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bernhard Preim

This figure shows the co-authorship network connecting the top 25 collaborators of Bernhard Preim. A scholar is included among the top collaborators of Bernhard Preim 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 Bernhard Preim. Bernhard Preim 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

Preim, Bernhard, et al.. (2025). Multilabel segmentation and analysis of skeletal muscle and adipose tissue in routine abdominal CT scans. Computers in Biology and Medicine. 186. 109622–109622. 1 indexed citations

Meuschke, Monique, et al.. (2025). A survey of intracranial aneurysm detection and segmentation. Medical Image Analysis. 101. 103493–103493. 1 indexed citations

Preim, Bernhard, et al.. (2024). Virtual radionuclide laboratory: An e-learning solution for a tailored training event. Nuclear Engineering and Design. 423. 113173–113173. 1 indexed citations

Bäumler, Kathrin, Domenico Mastrodicasa, Veit Sandfort, et al.. (2024). Advanced visualization of aortic dissection anatomy and hemodynamics. Computers & Graphics. 124. 104060–104060.

Huber, Tobias, Florentine Huettl, Vuthea Chheang, et al.. (2024). Virtual Reality in der Leberchirurgie – Planen, Weiterbilden, Prüfen. Die Chirurgie. 96(1). 16–22.

Wolf, Ivo, et al.. (2024). Surgical phase and instrument recognition: how to identify appropriate dataset splits. International Journal of Computer Assisted Radiology and Surgery. 19(4). 699–711. 2 indexed citations

Huettl, Florentine, Patrick Saalfeld, M. Paschold, et al.. (2021). Using virtual 3D-models in surgical planning: workflow of an immersive virtual reality application in liver surgery. Langenbeck s Archives of Surgery. 406(3). 911–915. 53 indexed citations

Niemann, Uli, et al.. (2020). Combining visual analytics and case-based reasoning for rupture risk assessment of intracranial aneurysms. International Journal of Computer Assisted Radiology and Surgery. 15(9). 1525–1535. 7 indexed citations

Voß, Samuel, Oliver Beuing, Katja Jachau, et al.. (2016). Fluid-Structure Simulations of a Ruptured Intracranial Aneurysm: Constant versus Patient-Specific Wall Thickness. Computational and Mathematical Methods in Medicine. 2016. 1–8. 51 indexed citations

10.

Berg, Philipp, et al.. (2015). Reconstruction of 3D Surface Meshes for Bood Flow Simulations of Intracranial Aneurysms.. 163–168. 7 indexed citations

11.

Oeltze, Steffen, et al.. (2011). Interactive, Graph-based Visual Analysis of High-dimensional, Multi-parameter Fluorescence Microscopy Data in Toponomics. IEEE Transactions on Visualization and Computer Graphics. 17(12). 1882–1891. 9 indexed citations

12.

Stavrou, Gregor A., et al.. (2011). Der LiverSurgeryTrainer - Ein chirurgisches Trainingssystem für die Planung von Eingriffen an der Leber. 99–104. 1 indexed citations

13.

Preim, Bernhard, et al.. (2010). Günstige Kamerapfade für medizinische Animationen.. 46–50. 2 indexed citations

14.

Boehm, Andreas, Stefan C. Mueller, Gero Strauß, et al.. (2010). TTM Tumor Therapy Manager. 17–20. 2 indexed citations

15.

Preim, Bernhard, et al.. (2009). Szenariobasierte Entwicklung von Systemen für Training und Planung in der ChirurgieScenario-Based Design of Surgical Training and Planning Systems. i-com. 8(1). 5–12. 1 indexed citations

16.

Born, Silvia, et al.. (2008). Bildanalyse, Visualisierung und Modellerstellung für die Implantatplanung im Mittelohr.. 139–154.

17.

Neugebauer, Mathias, Gábor Janiga, Stefan Zachow, Martin Skalej, & Bernhard Preim. (2008). Generierung qualitativ hochwertiger Modelle für die Simulation von Bluttfluss in zerebralen Aneurysmen.. 221–236. 2 indexed citations

18.

Preim, Bernhard & Dirk Bartz. (2007). Visualization in Medicine: Theory, Algorithms, and Applications. Morgan Kaufmann Publishers Inc. eBooks. 680–680. 85 indexed citations

19.

Kühnel, Caroline, Anja Hennemuth, Tobias Boskamp, et al.. (2006). New Software Assistants for Cardiovascular Diagnosis.. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 491–498. 4 indexed citations

20.

Preim, Bernhard, et al.. (2000). Interaktive medizinische Volumenvisualisierung - ein Überblick.. 69–88. 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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