Chen Qin

2.5k citations
68 papers · 1.6k · 1 hit paper · h-index 19

Impact in

Papers in

Chen Qin

62 papers receiving 1.6k citations

Chen Qin's Hit Papers

Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction 2018 · 447 citations
4470+2+5Years since publication100200300400

Peers

Chen Qin
Comparison fields: 5 of 97
  • Radiology, Nuclear Medicine and Imaging 849
  • Computer Vision and Pattern Recognition 516
  • Health Informatics 15
  • Neurology 77
  • Artificial Intelligence 310
Replace Ali Gooya with:
Ali Gooya United Kingdom
Jingfan Fan China
Mingfeng Jiang China
Kerstin Hammernik Germany
Joseph Y. Cheng United States
François Lauze Denmark
Jiliu Zhou China
Javad Alirezaie Canada
Jeny Rajan India
Jinming Duan United Kingdom
Chen Qin relative to Ali Gooya United Kingdom Ali Gooya's profile →
Citations per field
00.5×2×3×4×4.7×
Ali Gooya · 1×
Citations per year

Countries citing papers authored by Chen Qin

Since Specialization
Citations

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

Fields of papers citing papers by Chen Qin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 68 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction
Hit paper breakdown →
2018447
2 2018107
3 2021103
4 201995
5 201886
6 202068
7 202158
8 201957
9 201739
10 202336
11 202236
12 202134
13 201634
14 201830
15 201824
16 201921
17 201921
18 202221
19 201720
20 201318

About Chen Qin

Chen Qin is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Artificial Intelligence, Biomedical Engineering and Neurology, having authored 68 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced MRI Techniques and Applications (22 papers), Medical Imaging Techniques and Applications (16 papers), Medical Image Segmentation Techniques (15 papers), Advanced Neural Network Applications (8 papers), Cardiac Imaging and Diagnostics (6 papers), Domain Adaptation and Few-Shot Learning (4 papers), Brain Tumor Detection and Classification (4 papers) and Advanced X-ray and CT Imaging (3 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (849 citations), Computer Vision and Pattern Recognition (516 citations), Health Informatics (15 citations), Neurology (77 citations) and Artificial Intelligence (310 citations). Chen Qin has collaborated with scholars based in United Kingdom, China and Germany. Frequent co-authors include Daniel Rueckert, Jo Schlemper, Joseph V. Hajnal, Anthony N. Price, José Caballero, Wenjia Bai, Jinming Duan, Giacomo Tarroni, Chen Chen and Shuo Wang. Their work appears in journals such as IEEE Transactions on Medical Imaging, Medical Image Analysis, Lecture notes in computer science, IEEE Transactions on Computational Imaging and Magnetic Resonance in 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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