G. Krämer

920 total citations
24 papers, 682 citations indexed

About

G. Krämer is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Genetics. According to data from OpenAlex, G. Krämer has authored 24 papers receiving a total of 682 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Radiology, Nuclear Medicine and Imaging, 11 papers in Pulmonary and Respiratory Medicine and 3 papers in Genetics. Recurrent topics in G. Krämer's work include Medical Imaging Techniques and Applications (15 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and Prostate Cancer Treatment and Research (7 papers). G. Krämer is often cited by papers focused on Medical Imaging Techniques and Applications (15 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and Prostate Cancer Treatment and Research (7 papers). G. Krämer collaborates with scholars based in Netherlands, United Kingdom and United States. G. Krämer's co-authors include Ronald Boellaard, Otto S. Hoekstra, Egbert F. Smit, Virginie Frings, Adrianus J. de Langen, Floris H. P. van Velden, Emma R. Mulder, Ida A. Nissen, Ludwig Gutmann and Matthijs C. F. Cysouw and has published in prestigious journals such as Neurology, European Urology and European Journal of Cancer.

In The Last Decade

G. Krämer

22 papers receiving 674 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
G. Krämer Netherlands 12 480 244 138 93 47 24 682
David Kersting Germany 14 314 0.7× 149 0.6× 90 0.7× 128 1.4× 2 0.0× 59 589
Baixuan Xu China 12 216 0.5× 148 0.6× 46 0.3× 91 1.0× 63 448
Chong Jiang China 16 148 0.3× 292 1.2× 41 0.3× 98 1.1× 4 0.1× 46 810
Caiyuan Zhang China 12 191 0.4× 47 0.2× 74 0.5× 84 0.9× 3 0.1× 28 427
Jieheng Wu China 13 50 0.1× 135 0.6× 28 0.2× 132 1.4× 17 0.4× 26 492
Jianye Liang China 16 312 0.7× 107 0.4× 62 0.4× 27 0.3× 30 488
Juliet A. Wendt United States 8 194 0.4× 72 0.3× 173 1.3× 160 1.7× 10 531
Zhaoyu Xing China 10 177 0.4× 166 0.7× 51 0.4× 68 0.7× 24 370
Sonya Youngju Park South Korea 12 166 0.3× 177 0.7× 16 0.1× 73 0.8× 34 387

Countries citing papers authored by G. Krämer

Since Specialization
Citations

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

Fields of papers citing papers by G. Krämer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of G. Krämer

This figure shows the co-authorship network connecting the top 25 collaborators of G. Krämer. A scholar is included among the top collaborators of G. Krämer 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 G. Krämer. G. Krämer 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.
García, David Vállez, G. Krämer, Virginie Frings, et al.. (2021). Effects of Tracer Uptake Time in Non–Small Cell Lung Cancer18F-FDG PET Radiomics. Journal of Nuclear Medicine. 63(6). 919–924. 9 indexed citations
3.
Cysouw, Matthijs C. F., Sandeep S.V. Golla, Verena Frings, et al.. (2019). Partial-volume correction in dynamic PET-CT: effect on tumor kinetic parameter estimation and validation of simplified metrics. EJNMMI Research. 9(1). 12–12. 16 indexed citations
4.
Jansen, B.H.E., Maqsood Yaqub, Jens Voortman, et al.. (2019). Simplified Methods for Quantification of 18F-DCFPyL Uptake in Patients with Prostate Cancer. Journal of Nuclear Medicine. 60(12). 1730–1735. 27 indexed citations
5.
Krämer, G., Maqsood Yaqub, H. Alberto Vargas, et al.. (2019). Assessment of Simplified Methods for Quantification of 18F-FDHT Uptake in Patients with Metastatic Castration-Resistant Prostate Cancer. Journal of Nuclear Medicine. 60(9). 1221–1227. 9 indexed citations
6.
García, David Vállez, G. Krämer, Virginie Frings, et al.. (2019). Repeatability of [18F]FDG PET/CT total metabolic active tumour volume and total tumour burden in NSCLC patients. EJNMMI Research. 9(1). 14–14. 27 indexed citations
7.
Cysouw, Matthijs C. F., G. Krämer, Dennis Heijtel, et al.. (2019). Sensitivity of 18F-fluorodihydrotestosterone PET-CT to count statistics and reconstruction protocol in metastatic castration-resistant prostate cancer. EJNMMI Research. 9(1). 70–70. 8 indexed citations
8.
Leisser, Asha, Markus Hartenbach, Heying Duan, et al.. (2019). Hematopoiesis is prognostic for toxicity and survival of 223Radium treatment in patients with metastatic castration-resistant prostate cancer.. PubMed. 20 Suppl. 157–157.
9.
Krämer, G., Adrianus J. de Langen, Elise P. Jansma, et al.. (2018). Repeatability of quantitative 18F-FLT uptake measurements in solid tumors: an individual patient data multi-center meta-analysis. European Journal of Nuclear Medicine and Molecular Imaging. 45(6). 951–961. 7 indexed citations
10.
11.
García, David Vállez, G. Krämer, Virginie Frings, et al.. (2018). Variability and Repeatability of Quantitative Uptake Metrics in 18F-FDG PET/CT of Non–Small Cell Lung Cancer: Impact of Segmentation Method, Uptake Interval, and Reconstruction Protocol. Journal of Nuclear Medicine. 60(5). 600–607. 18 indexed citations
12.
Slart, Riemer H. J. A., Douwe J. Mulder, Ronald Borra, et al.. (2018). Performance Evaluation of a Semi-automated Method for [18F]FDG Uptake in Abdominal Visceral Adipose Tissue. Molecular Imaging and Biology. 21(1). 159–167. 4 indexed citations
13.
Cysouw, Matthijs C. F., G. Krämer, Virginie Frings, et al.. (2017). Baseline and longitudinal variability of normal tissue uptake values of [ 18 F]-fluorothymidine-PET images. Nuclear Medicine and Biology. 51. 18–24. 3 indexed citations
14.
Cysouw, Matthijs C. F., G. Krämer, Otto S. Hoekstra, et al.. (2016). Accuracy and Precision of Partial-Volume Correction in Oncological PET/CT Studies. Journal of Nuclear Medicine. 57(10). 1642–1649. 30 indexed citations
15.
Krämer, G., Virginie Frings, Nikie J. Hoetjes, et al.. (2016). Repeatability of Quantitative Whole-Body 18F-FDG PET/CT Uptake Measures as Function of Uptake Interval and Lesion Selection in Non–Small Cell Lung Cancer Patients. Journal of Nuclear Medicine. 57(9). 1343–1349. 49 indexed citations
16.
Schelhaas, Sonja, Kathrin Heinzmann, Vikram Rao Bollineni, et al.. (2016). Preclinical Applications of 3'-Deoxy-3'-[18F] Fluoro-thymidine in Oncology - A Systematic Review. Theranostics. 7(1). 40–50. 24 indexed citations
17.
Velden, Floris H. P. van, G. Krämer, Virginie Frings, et al.. (2016). Repeatability of Radiomic Features in Non-Small-Cell Lung Cancer [18F]FDG-PET/CT Studies: Impact of Reconstruction and Delineation. Molecular Imaging and Biology. 18(5). 788–795. 217 indexed citations
18.
19.
Bollineni, Vikram Rao, et al.. (2015). A literature review of the association between diffusion-weighted MRI derived apparent diffusion coefficient and tumour aggressiveness in pelvic cancer. Cancer Treatment Reviews. 41(6). 496–502. 40 indexed citations
20.
Djavan, Bob, Alexandre R. Zlotta, Samuel Ekane, et al.. (2000). Is One Set of Sextant Biopsies Enough to Rule Out Prostate Cancer? Influence of Transition and Total Prostate Volumes on Prostate Cancer Yield. European Urology. 38(2). 218–224. 63 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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