Haojun Yu

1.9k citations
68 papers · 1.2k indexed · 1 hit paper · h-index 19

Haojun Yu

65 papers receiving 1.1k citations

Hit Papers

DETRs with Hybrid Matching12720232026202420254080120

Peers

Haojun Yu
Comparison fields: 5 of 95
  • Radiology, Nuclear Medicine and Imaging 837
  • Radiation 163
  • Biomedical Engineering 285
  • Pulmonary and Respiratory Medicine 211
  • Computer Vision and Pattern Recognition 102
Replace Tyler Bradshaw with:
Tyler Bradshaw United States
Jifke F. Veenland Netherlands
Avishek Chatterjee Netherlands
Ida Häggström United States
Alessandro Stefano Italy
Magda Marcon Switzerland
Thomas Wendler Germany
Pieter Slagmolen Belgium
Soumya Ghose United States
Guanzhong Gong China
Haojun Yu relative to Tyler Bradshaw United States Tyler Bradshaw's profile →
Citations per field
00.5×1.6×
Tyler Bradshaw · 1×
Citations per year

Countries citing papers authored by Haojun Yu

Since Specialization
Citations

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

Fields of papers citing papers by Haojun Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20241
3 20243
4 20235
5 20235
6 202312
7 202322
8 20232
9 20232
10 20239
11 202214
12 202217
13 20228
14 202225
15 202169
16 202110
17 202112
18 202029
19 201555
20 201132

About Haojun Yu

Haojun Yu is a scholar working on Radiology, Nuclear Medicine and Imaging, Radiation and Pulmonary and Respiratory Medicine, having authored 68 papers that have together received 1.2k indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (44 papers), Radiomics and Machine Learning in Medical Imaging (27 papers), Advanced X-ray and CT Imaging (19 papers), Advanced MRI Techniques and Applications (9 papers), MRI in cancer diagnosis (7 papers), Radiation Dose and Imaging (7 papers), Radiopharmaceutical Chemistry and Applications (6 papers) and Cardiac Imaging and Diagnostics (5 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (837 citations), Radiation (163 citations) and Biomedical Engineering (285 citations). Haojun Yu has collaborated with scholars based in China, United States and South Sudan. Frequent co-authors include Pengcheng Hu, Hui Tan, Yiqiu Zhang, Hongcheng Shi, Hongcheng Shi, Guobing Liu, Shuguang Chen, Wujian Mao, Yushen Gu and Hongyan Yin. Their work appears in journals such as European Journal of Nuclear Medicine and Molecular Imaging, EJNMMI Physics, Nuclear Medicine Communications, European Radiology and Annals of Nuclear Medicine.

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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