Tie Liang
Impact in
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- MRI in cancer diagnosis
-
- Hepatocellular Carcinoma Treatment and Prognosis
Papers in
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- Medical Imaging Techniques and Applications 7
- Radiomics and Machine Learning in Medical Imaging 7
- Radiopharmaceutical Chemistry and Applications 6
- MRI in cancer diagnosis 4
- Co-authors
- Craig S. WellsHeike E. Daldrup‐LinkAshok J. TheruvathJustin R. TseAya KamayaAndrei IagaruGuido DavidzonRonald K. Hambleton
- Journals
- Abdominal Radiology (8 papers)Journal of Nuclear Medicine (3 papers)American Journal of Roentgenology (3 papers)Scientific Reports (2 papers)European Radiology (2 papers)
- Partner nations
- United StatesGermanySouth Korea
In The Last Decade
Tie Liang
42 papers receiving 480 citations
Peers
Comparison fields: 5 of 92
- Radiology, Nuclear Medicine and Imaging 147
- Hepatology 44
- Internal Medicine 17
- Management Science and Operations Research 39
- Biomedical Engineering 139
Countries citing papers authored by Tie Liang
This map shows the geographic impact of Tie Liang'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 Tie Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tie Liang more than expected).
Fields of papers citing papers by Tie Liang
This network shows the impact of papers produced by Tie Liang. 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 Tie Liang. The network helps show where Tie Liang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Tie Liang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 9 | |
| 4 | 2024 | 3 | |
| 5 | 2023 | 7 | |
| 6 | 2023 | 3 | |
| 7 | 2023 | 1 | |
| 8 | 2023 | 2 | |
| 9 | 2023 | 0 | |
| 10 | 2022 | 8 | |
| 11 | 2022 | 6 | |
| 12 | 2021 | 96 | |
| 13 | 2021 | 6 | |
| 14 | 2021 | 4 | |
| 15 | 2021 | 14 | |
| 16 | 2021 | 10 | |
| 17 | 2020 | 30 | |
| 18 | 2019 | 31 | |
| 19 | 2019 | 13 | |
| 20 | 2018 | 11 |
About Tie Liang
Tie Liang is a scholar working on Radiology, Nuclear Medicine and Imaging, Internal Medicine, Hepatology, Pulmonary and Respiratory Medicine and Management Science and Operations Research, having authored 51 papers that have together received 494 indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (7 papers), Radiomics and Machine Learning in Medical Imaging (7 papers), Radiopharmaceutical Chemistry and Applications (6 papers), Renal cell carcinoma treatment (5 papers), Prostate Cancer Treatment and Research (5 papers), MRI in cancer diagnosis (4 papers), Liver Disease and Transplantation (4 papers) and Hepatocellular Carcinoma Treatment and Prognosis (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (147 citations), Hepatology (44 citations), Internal Medicine (17 citations), Management Science and Operations Research (39 citations) and Biomedical Engineering (139 citations). Tie Liang has collaborated with scholars based in United States, Germany and South Korea. Frequent co-authors include Craig S. Wells, Heike E. Daldrup‐Link, Ashok J. Theruvath, Justin R. Tse, Aya Kamaya, Andrei Iagaru, Guido Davidzon, Ronald K. Hambleton, Eun-Yeong Park and Alina A. von Davier. Their work appears in journals such as Abdominal Radiology, Journal of Nuclear Medicine, American Journal of Roentgenology, Scientific Reports and European Radiology.
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.