Daniel Labar

2.1k citations
52 papers · 1.8k · h-index 22

Impact in

Papers in

Daniel Labar

51 papers receiving 1.7k citations

Peers

Daniel Labar
Comparison fields: 5 of 64
  • Radiology, Nuclear Medicine and Imaging 732
  • Cancer Research 121
  • Pharmaceutical Science 51
  • Radiation 54
  • Cognitive Neuroscience 79
Replace H.‐J. Machulla with:
H.‐J. Machulla Germany
Joseph C. Walsh United States
Peter J. Julyan United Kingdom
H.-J. Machulla Germany
Jonas Eriksson Sweden
Wendy A. Waddington United Kingdom
Michele Melia United States
Sajinder Kaur Luthra United Kingdom
Elaine M. Jagoda United States
Tobias L. Roß Germany
Daniel Labar relative to H.‐J. Machulla Germany H.‐J. Machulla's profile →
Citations per field
00.5×2×3×3.8×
H.‐J. Machulla · 1×
Citations per year

Countries citing papers authored by Daniel Labar

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Labar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel Labar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Labar Line = papers co-authored together Daniel Labar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003202
2 1996175
3 2000162
4 199993
5 201386
6 201485
7 200278
8 201471
9 199165
10 201264
11 201550
12 200149
13 201748
14 200843
15
Synthesis of [2-11C] thymidine : an imaging agent for cellular proliferation.
199042
16 201434
17 201033
18 201433
19 200832
20 201426

About Daniel Labar

Daniel Labar is a scholar working on Radiology, Nuclear Medicine and Imaging, Cancer Research, Radiation, Hepatology and Toxicology, having authored 52 papers that have together received 1.8k indexed citations. Recurring topics across this work include Radiopharmaceutical Chemistry and Applications (15 papers), Medical Imaging Techniques and Applications (4 papers), Cancer, Hypoxia, and Metabolism (3 papers), Liver physiology and pathology (2 papers), Cardiac Imaging and Diagnostics (2 papers), Advanced MRI Techniques and Applications (2 papers), Advanced Radiotherapy Techniques (2 papers) and Epilepsy research and treatment (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (732 citations), Cancer Research (121 citations), Pharmaceutical Science (51 citations), Radiation (54 citations) and Cognitive Neuroscience (79 citations). Daniel Labar has collaborated with scholars based in Belgium, France and United States. Frequent co-authors include Anne Bol, Vincent Grégoire, Christian Jean Michel, Anne De Volder, Thierry Vander Borght, John A. Lee, Merence Sibomana, Bernard Gallez, Stanislas A. Pauwels and Jean‐Louis Vanoverschelde. Their work appears in journals such as European Journal of Nuclear Medicine and Molecular Imaging, Journal of Nuclear Medicine, Radiotherapy and Oncology, Acta Oncologica and Contrast Media & Molecular Imaging.

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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