Kun Lu

969 citations
23 papers · 660 · h-index 12

Impact in

Papers in

Kun Lu

21 papers receiving 653 citations

Peers

Kun Lu
Comparison fields: 5 of 70
  • Radiology, Nuclear Medicine and Imaging 319
  • Cognitive Neuroscience 241
  • Neurology 86
  • Neurology 31
  • Cellular and Molecular Neuroscience 70
Replace Neda Sadeghi with:
Neda Sadeghi United States
Gavin C. Houston United Kingdom
Joanna E. Perthen United States
Renata Ferranti Leoni Brazil
Rebecca Quest United Kingdom
Heidi Gröhn Finland
Joonas A. Autio Japan
Hiromasa Takemura Japan
Abid Qureshi United States
Kun Lu relative to Neda Sadeghi United States Neda Sadeghi's profile →
Citations per field
00.5×1.5×1.8×
Neda Sadeghi · 1×
Citations per year

Countries citing papers authored by Kun Lu

Since Specialization
Citations

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

Fields of papers citing papers by Kun Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Kun Lu, 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 Kun Lu Line = papers co-authored together Kun Lu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010217
2 200499
3 201374
4 201666
5 202226
6 201524
7 200720
8 202219
9 200816
10 202216
11 202112
12 202211
13 202211
14 202211
15 20229
16 20226
17 20076
18 20156
19 20145
20 20234

About Kun Lu

Kun Lu is a scholar working on Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience, Ophthalmology, Epidemiology and Neurology, having authored 23 papers that have together received 660 indexed citations. Recurring topics across this work include Advanced MRI Techniques and Applications (8 papers), Functional Brain Connectivity Studies (6 papers), Advanced Neuroimaging Techniques and Applications (5 papers), MRI in cancer diagnosis (2 papers), Retinal Imaging and Analysis (2 papers), Glaucoma and retinal disorders (2 papers), Ultrasound Imaging and Elastography (1 paper) and Fetal and Pediatric Neurological Disorders (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (319 citations), Cognitive Neuroscience (241 citations), Neurology (86 citations), Neurology (31 citations) and Cellular and Molecular Neuroscience (70 citations). Kun Lu has collaborated with scholars based in United States, China and Netherlands. Frequent co-authors include Thomas T. Liu, Richard B. Buxton, Joseph B. Mandeville, Helen D’Arceuil, Alex J. de Crespigny, Bruce R. Rosen, Peifang Tian, David A. Boas, John J.A. Marota and Elizabeth M. C. Hillman. Their work appears in journals such as Frontiers in Aging Neuroscience, Current Neurovascular Research, CNS Neuroscience & Therapeutics, Scientific Reports and Neurocritical Care.

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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