Ulf Neuberger

1.9k total citations · 1 hit paper
15 papers, 761 citations indexed

About

Ulf Neuberger is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics and Molecular Biology. According to data from OpenAlex, Ulf Neuberger has authored 15 papers receiving a total of 761 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Radiology, Nuclear Medicine and Imaging, 8 papers in Genetics and 2 papers in Molecular Biology. Recurrent topics in Ulf Neuberger's work include Glioma Diagnosis and Treatment (8 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and MRI in cancer diagnosis (3 papers). Ulf Neuberger is often cited by papers focused on Glioma Diagnosis and Treatment (8 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and MRI in cancer diagnosis (3 papers). Ulf Neuberger collaborates with scholars based in Germany, United States and Austria. Ulf Neuberger's co-authors include Martin Bendszus, Wolfgang Wick, Philipp Kickingereder, David Bonekamp, Klaus Maier‐Hein, Antje Wick, Gianluca Brugnara, Sabine Heiland, Heinz‐Peter Schlemmer and Fabian Isensee and has published in prestigious journals such as Clinical Cancer Research, Human Brain Mapping and American Journal of Neuroradiology.

In The Last Decade

Ulf Neuberger

14 papers receiving 753 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Automated brain extraction of multisequence MRI using artificial neural networks

2019 364 citations Fabian Isensee, Marianne Schell et al. Human Brain Mapping profile →

Peers

Ulf Neuberger

RNMI

GENET

PRM

NEURO

Barbara Bobek‐Billewicz Poland

Hassan Bagher‐Ebadian United States

Gianluca Brugnara Germany

Luke Macyszyn United States

Anahita Fathi Kazerooni United States

Marc C. Mabray United States

Jared Pisapia United States

Virginia Hill United States

Chad A. Holder United States

Barbara Bobek‐Billewicz Poland

Ulf Neuberger

289 ×0.6

RNMI

205 ×0.7

GENET

108 ×0.8

PRM

131 ×1.4

NEURO

63 ×0.8

NEURO

Citations per year, relative to Ulf Neuberger Ulf Neuberger (= 1×) peers Barbara Bobek‐Billewicz

Countries citing papers authored by Ulf Neuberger

Since Specialization

Citations

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

Fields of papers citing papers by Ulf Neuberger

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ulf Neuberger

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

All Works

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15 of 15 papers shown

Foltyn, Martha, Ulf Neuberger, Felix Sahm, et al.. (2024). Unraveling glioblastoma diversity: Insights into methylation subtypes and spatial relationships. Neuro-Oncology Advances. 6(1). vdae112–vdae112.

Strasser, Bernhard, Ulf Neuberger, Philipp Kickingereder, et al.. (2022). Deep learning super-resolution magnetic resonance spectroscopic imaging of brain metabolism and mutant isocitrate dehydrogenase glioma. Neuro-Oncology Advances. 4(1). vdac071–vdac071. 6 indexed citations

Weyland, Charlotte S., Ulf Neuberger, Arne Potreck, et al.. (2020). Reasons for Failed Mechanical Thrombectomy in Posterior Circulation Ischemic Stroke Patients. Clinical Neuroradiology. 31(3). 745–752. 15 indexed citations

Schell, Marianne, Gianluca Brugnara, Fabian Isensee, et al.. (2020). Validation of diffusion MRI phenotypes for predicting response to bevacizumab in recurrent glioblastoma: post-hoc analysis of the EORTC-26101 trial. Neuro-Oncology. 22(11). 1667–1676. 9 indexed citations

Brugnara, Gianluca, Fabian Isensee, Ulf Neuberger, et al.. (2020). Automated volumetric assessment with artificial neural networks might enable a more accurate assessment of disease burden in patients with multiple sclerosis. European Radiology. 30(4). 2356–2364. 19 indexed citations

Foltyn, Martha, Ulf Neuberger, Gianluca Brugnara, et al.. (2020). T2/FLAIR-mismatch sign for noninvasive detection of IDH-mutant 1p/19q non-codeleted gliomas: validity and pathophysiology. Neuro-Oncology Advances. 2(1). vdaa004–vdaa004. 34 indexed citations

Laible, Mona, Ekkehart Jenetzky, Markus Möhlenbruch, et al.. (2019). Renal Impairment Is Associated with Intracerebral Hemorrhage after Mechanical Thrombectomy in Vertebrobasilar Stroke. Cerebrovascular Diseases. 47(1-2). 48–56. 22 indexed citations

Foltyn, Martha, Ulf Neuberger, Annekathrin Reinhardt, et al.. (2019). NIMG-02. NON-INVASIVE DETECTION OF IDH MUTANT 1p19q NON-CODELETED GLIOMAS USING THE T2-FLAIR MISMATCH SIGN. Neuro-Oncology. 21(Supplement_6). vi161–vi161. 1 indexed citations

Isensee, Fabian, Marianne Schell, Gianluca Brugnara, et al.. (2019). Automated brain extraction of multisequence MRI using artificial neural networks. Human Brain Mapping. 40(17). 4952–4964. 364 indexed citations breakdown →

10.

Vollherbst, Dominik F., Christian Ulfert, Ulf Neuberger, et al.. (2018). Endovascular Treatment of Dural Arteriovenous Fistulas Using Transarterial Liquid Embolization in Combination with Transvenous Balloon-Assisted Protection of the Venous Sinus. American Journal of Neuroradiology. 39(7). 1296–1302. 21 indexed citations

11.

Neuberger, Ulf, Annekathrin Reinhardt, Gianluca Brugnara, et al.. (2018). Voxel-wise radiogenomic mapping of tumor location with key molecular alterations in patients with glioma. Neuro-Oncology. 20(11). 1517–1524. 32 indexed citations

12.

Neuberger, Ulf, Philipp Kickingereder, Xavier Helluy, et al.. (2017). Accuracy of 1H magnetic resonance spectroscopy for quantification of 2-hydroxyglutarate using linear combination and J-difference editing at 9.4 T. Zeitschrift für Medizinische Physik. 27(4). 300–309. 2 indexed citations

13.

Neuberger, Ulf, et al.. (2017). Severe Ocular Myositis After Ipilimumab Treatment for Melanoma: A Report of 2 Cases. Journal of Immunotherapy. 40(7). 282–285. 28 indexed citations

14.

Kickingereder, Philipp, Michael Götz, John Muschelli, et al.. (2016). Large-scale Radiomic Profiling of Recurrent Glioblastoma Identifies an Imaging Predictor for Stratifying Anti-Angiogenic Treatment Response. Clinical Cancer Research. 22(23). 5765–5771. 206 indexed citations

15.

Kickingereder, Philipp, Michael Götz, Antje Wick, et al.. (2016). OS4.6 Large-scale radiomic profiling of recurrent glioblastoma identifies an imaging predictor for stratifying anti-angiogenic treatment response. Neuro-Oncology. 18(suppl_4). iv10–iv10. 2 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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