Peixi Liao
- Radiology, Nuclear Medicine and Imaging top 0.5%
- Biomedical Engineering top 2%
- Computer Vision and Pattern Recognition top 1%
- Radiation top 5%
- Artificial Intelligence top 10%
- Topics
- Advanced X-ray and CT Imaging (12 papers)Medical Imaging Techniques and Applications (11 papers)Dental Radiography and Imaging (9 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingComputer Vision and Pattern RecognitionBiomedical Engineering
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Peixi Liao
26 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 106
- Radiology, Nuclear Medicine and Imaging 1.9k
- Biomedical Engineering 1.4k
- Computer Vision and Pattern Recognition 722
- Radiation 174
- Artificial Intelligence 172
Countries citing papers authored by Peixi Liao
This map shows the geographic impact of Peixi Liao'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 Peixi Liao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peixi Liao more than expected).
Fields of papers citing papers by Peixi Liao
This network shows the impact of papers produced by Peixi Liao. 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 Peixi Liao. The network helps show where Peixi Liao may publish in the future.
Co-authorship network of co-authors of Peixi Liao
This figure shows the co-authorship network connecting the top 25 collaborators of Peixi Liao. A scholar is included among the top collaborators of Peixi Liao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Peixi Liao. Peixi Liao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 13 | |
| 7 | 9 | |
| 8 | 8 | |
| 9 | 2 | |
| 10 | 6 | |
| 11 | 1 | |
| 12 | 1 | |
| 13 | 31 | |
| 14 | 10 | |
| 15 | 24 | |
| 16 | Learned Experts' Assessment-based Reconstruction Network ("LEARN") for Sparse-data CT. | 3 |
| 17 | Low-Dose CT With a Residual Encoder-Decoder Convolutional Neural Networkbreakdown → | 1209 |
| 18 | 20 | |
| 19 | aLow-dose CT via convolutional neural networkbreakdown → | 515 |
| 20 | The effect of chronic periodontitis on serum levels of matrix metalloproteinase-2 (MMP-2), tissue inhibitor of metalloproteinase-1 (TIMP-1), interleukin-12 (IL-12) and granulocyte-macrophage colony-stimulating factor (GM-CSF) | 3 |
About Peixi Liao
Peixi Liao is a scholar working on Oral Surgery, General Dentistry and Archeology, having authored 29 papers that have together received 2.4k indexed citations. Recurring topics across this work include Advanced X-ray and CT Imaging (12 papers), Medical Imaging Techniques and Applications (11 papers) and Dental Radiography and Imaging (9 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (1.9k citations), Computer Vision and Pattern Recognition (722 citations) and Biomedical Engineering (1.4k citations). Peixi Liao has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Hu Chen, Yi Zhang, Ge Wang, Jiliu Zhou, Feng Lin, Mannudeep K. Kalra, Yang Chen, Ke Li, Weihua Zhang and Huaiqiang Sun. Their work appears in journals such as PLoS ONE, IEEE Transactions on Medical Imaging and Journal of Endodontics.
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.