Ursula Kohlhofer

984 total citations
30 papers, 663 citations indexed

About

Ursula Kohlhofer is a scholar working on Radiology, Nuclear Medicine and Imaging, Molecular Biology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Ursula Kohlhofer has authored 30 papers receiving a total of 663 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Radiology, Nuclear Medicine and Imaging, 8 papers in Molecular Biology and 5 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Ursula Kohlhofer's work include Medical Imaging Techniques and Applications (6 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and MRI in cancer diagnosis (3 papers). Ursula Kohlhofer is often cited by papers focused on Medical Imaging Techniques and Applications (6 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and MRI in cancer diagnosis (3 papers). Ursula Kohlhofer collaborates with scholars based in Germany, United States and Japan. Ursula Kohlhofer's co-authors include Leticia Quintanilla-Martı́nez, Bernd J. Pichler, Manfred Kneilling, Gerald Reischl, Stefan Wiehr, Julia G. Mannheim, Jonathan A. Disselhorst, Kerstin Fuchs, Jakob Voelkl and Florian Läng and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Blood.

In The Last Decade

Ursula Kohlhofer

30 papers receiving 661 citations

Peers

Ursula Kohlhofer
Wei Xiao China
Tatsuya Inoue Japan
Kathrine Woie Norway
Raquel Lima e Silva United States
Veronica Klepeis United States
Christopher T. Winkelmann United States
Zhen Zhao China
Marco De Giorgi Italy
Litao Sun China
Mohd Hafeez Faridi United States
Wei Xiao China
Ursula Kohlhofer
Citations per year, relative to Ursula Kohlhofer Ursula Kohlhofer (= 1×) peers Wei Xiao

Countries citing papers authored by Ursula Kohlhofer

Since Specialization
Citations

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

Fields of papers citing papers by Ursula Kohlhofer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ursula Kohlhofer

This figure shows the co-authorship network connecting the top 25 collaborators of Ursula Kohlhofer. A scholar is included among the top collaborators of Ursula Kohlhofer 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 Ursula Kohlhofer. Ursula Kohlhofer 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.
Schwenck, Johannes, Leonie Frauenfeld, Ursula Kohlhofer, et al.. (2023). Quantification of intratumoural heterogeneity in mice and patients via machine-learning models trained on PET–MRI data. Nature Biomedical Engineering. 7(8). 1014–1027. 9 indexed citations
2.
Montes‐Mojarro, Ivonne A., Julia Steinhilber, Christoph M. Griessinger, et al.. (2022). CD147 a direct target of miR-146a supports energy metabolism and promotes tumor growth in ALK+ ALCL. Leukemia. 36(8). 2050–2063. 9 indexed citations
3.
Schwab, Julian, Qian Chen, Anna Luisa Kühn, et al.. (2022). Intratumoral in vivo staging of breast cancer by multi-tracer PET and advanced analysis. npj Breast Cancer. 8(1). 41–41. 2 indexed citations
4.
Vega, Salvador Castaneda, Sandra Beer‐Hammer, Veronika Leiss, et al.. (2022). Cerebrovascular Gi Proteins Protect Against Brain Hypoperfusion and Collateral Failure in Cerebral Ischemia. Molecular Imaging and Biology. 25(2). 363–374. 4 indexed citations
5.
Vega, Salvador Castaneda, Francesca Maria Russo, Johann-Martin Hempel, et al.. (2021). Machine learning identifies stroke features between species. Theranostics. 11(6). 3017–3034. 15 indexed citations
6.
Naidu, Vegi M., Tamoghna Mandal, Ursula Kohlhofer, et al.. (2021). TET3 promotes AML growth and epigenetically regulates glucose metabolism and leukemic stem cell associated pathways. Leukemia. 36(2). 416–425. 28 indexed citations
7.
Bézière, Nicolas, Kerstin Fuchs, Andreas Maurer, et al.. (2019). Imaging fibrosis in inflammatory diseases: targeting the exposed extracellular matrix. Theranostics. 9(10). 2868–2881. 13 indexed citations
8.
Singh, Yogesh, Mohamed El-Hadidi, Jakob Admard, et al.. (2019). Enriched Environmental Conditions Modify the Gut Microbiome Composition and Fecal Markers of Inflammation in Parkinson’s Disease. Frontiers in Neuroscience. 13. 1032–1032. 19 indexed citations
9.
Märklin, Melanie, Jonas S. Heitmann, Michael Gutknecht, et al.. (2017). NFAT2 is a critical regulator of the anergic phenotype in chronic lymphocytic leukaemia. Nature Communications. 8(1). 755–755. 30 indexed citations
10.
Thunemann, Martin, Susanne Feil, Yun Lin, et al.. (2017). Cre/lox-assisted non-invasive in vivo tracking of specific cell populations by positron emission tomography. Nature Communications. 8(1). 444–444. 31 indexed citations
11.
Fuchs, Kerstin, Moritz Mahling, Andreas Hector, et al.. (2017). In Vivo Hypoxia PET Imaging Quantifies the Severity of Arthritic Joint Inflammation in Line with Overexpression of Hypoxia-Inducible Factor and Enhanced Reactive Oxygen Species Generation. Journal of Nuclear Medicine. 58(5). 853–860. 18 indexed citations
12.
Schmitz, Jennifer, Julian Schwab, Johannes Schwenck, et al.. (2016). Decoding Intratumoral Heterogeneity of Breast Cancer by Multiparametric In Vivo Imaging: A Translational Study. Cancer Research. 76(18). 5512–5522. 27 indexed citations
13.
14.
Leibrock, Christina, Martina Feger, Jakob Voelkl, et al.. (2016). Partial Reversal of Tissue Calcification and Extension of Life Span following Ammonium Nitrate Treatment of Klotho-Deficient Mice. Kidney & Blood Pressure Research. 41(1). 99–107. 12 indexed citations
15.
16.
Kohlhofer, Ursula, et al.. (2016). A Novel Unsupervised Segmentation Approach Quantifies Tumor Tissue Populations Using Multiparametric MRI: First Results with Histological Validation. Molecular Imaging and Biology. 19(3). 391–397. 15 indexed citations
17.
Kohlhofer, Ursula, et al.. (2016). Spectral Clustering Predicts Tumor Tissue Heterogeneity Using Dynamic 18F-FDG PET: A Complement to the Standard Compartmental Modeling Approach. Journal of Nuclear Medicine. 58(4). 651–657. 6 indexed citations
18.
Kohlhofer, Ursula, et al.. (2015). A Population-Based Gaussian Mixture Model Incorporating 18F-FDG PET and Diffusion-Weighted MRI Quantifies Tumor Tissue Classes. Journal of Nuclear Medicine. 57(3). 473–479. 29 indexed citations
19.
Leibrock, Christina, Jakob Voelkl, Ursula Kohlhofer, et al.. (2015). Bicarbonate-sensitive calcification and lifespan of klotho-deficient mice. American Journal of Physiology-Renal Physiology. 310(1). F102–F108. 16 indexed citations
20.
Bareiss, Petra M., Anna Paczulla, Hui Wang, et al.. (2013). SOX2 Expression Associates with Stem Cell State in Human Ovarian Carcinoma. Cancer Research. 73(17). 5544–5555. 126 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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