Haoteng Tang

421 citations
28 papers · 218 · h-index 10

Impact in

Papers in

Haoteng Tang

25 papers receiving 217 citations

Peers

Haoteng Tang
Comparison fields: 5 of 45
  • Radiology, Nuclear Medicine and Imaging 85
  • Cognitive Neuroscience 76
  • Health Informatics 5
  • Neurology 25
  • Computer Vision and Pattern Recognition 52
Replace Qiankun Zuo with:
Qiankun Zuo China
Vishnu Bashyam United States
Thi Kieu Khanh Ho South Korea
Debin Zeng China
Tzu-An Song United States
Roman Filipovych United States
Shunren Xia China
Nicola K. Dinsdale United Kingdom
Hejie Cui United States
Jiayue Cai China
Haoteng Tang relative to Qiankun Zuo China Qiankun Zuo's profile →
Citations per field
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Qiankun Zuo · 1×
Citations per year

Countries citing papers authored by Haoteng Tang

Since Specialization
Citations

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

Fields of papers citing papers by Haoteng Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Retrospective correction of motion artifact affected structural MRI images using deep learning of simulated motion
201828
2 201926
3 202225
4 202119
5 202318
6 202216
7 202016
8 202314
9 202310
10 20239
11 20228
12 20227
13 20235
14 20252
15 20232
16 20242
17 20252
18 20252
19 20251
20 20251

About Haoteng Tang

Haoteng Tang is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Artificial Intelligence, having authored 28 papers that have together received 218 indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (12 papers), Advanced Neuroimaging Techniques and Applications (7 papers), Mental Health Research Topics (5 papers), Medical Image Segmentation Techniques (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Advanced MRI Techniques and Applications (3 papers), EEG and Brain-Computer Interfaces (3 papers) and Brain Tumor Detection and Classification (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (85 citations), Cognitive Neuroscience (76 citations), Health Informatics (5 citations), Neurology (25 citations) and Computer Vision and Pattern Recognition (52 citations). Haoteng Tang has collaborated with scholars based in United States, China and Iran. Frequent co-authors include Liang Zhan, Heng Huang, Guixiang Ma, Meng Law, Hosung Kim, Ben A. Duffy, Paul M. Thompson, Lu Zhao, Lei Guo and Alex Leow. Their work appears in journals such as Computers in Biology and Medicine, Neural Networks, Magnetic Resonance in Medicine, Medical Image Analysis and Frontiers in Neuroinformatics.

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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