Thi-Thao Tran
Impact in
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- Medical Image Segmentation Techniques
- Advanced Neural Network Applications
- Image Retrieval and Classification Techniques
- Otorhinolaryngology top 10%
Papers in
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- Medical Image Segmentation Techniques 26
- Advanced Neural Network Applications 25
- Image Retrieval and Classification Techniques 8
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- AI in cancer detection 20
- Co-authors
- Van-Truong Pham (73 shared papers)Kuo‐Kai Shyu (15 shared papers)Men‐Tzung Lo (15 shared papers)Pa‐Chun Wang (5 shared papers)Po‐Lei Lee (4 shared papers)Chen Lin (6 shared papers)Lian‐Yu Lin (4 shared papers)Mao‐Yuan Su (3 shared papers)
In The Last Decade
Thi-Thao Tran
73 papers receiving 617 citations
Peers
Comparison fields: 5 of 86
- Computer Vision and Pattern Recognition 311
- Otorhinolaryngology 42
- Media Technology 64
- Neurology 45
- Radiology, Nuclear Medicine and Imaging 108
Countries citing papers authored by Thi-Thao Tran
This map shows the geographic impact of Thi-Thao Tran'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 Thi-Thao Tran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thi-Thao Tran more than expected).
Fields of papers citing papers by Thi-Thao Tran
This network shows the impact of papers produced by Thi-Thao Tran. 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 Thi-Thao Tran. The network helps show where Thi-Thao Tran may publish in the future.
Co-authors
The 25 scholars most cited alongside Thi-Thao Tran, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 76 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 49 | |
| 2 | 2011 | 36 | |
| 3 | 2024 | 36 | |
| 4 | 2018 | 31 | |
| 5 | 2023 | 30 | |
| 6 | 2014 | 28 | |
| 7 | 2020 | 26 | |
| 8 | 2015 | 24 | |
| 9 | 2011 | 21 | |
| 10 | 2023 | 21 | |
| 11 | 2022 | 21 | |
| 12 | 2019 | 18 | |
| 13 | 2022 | 17 | |
| 14 | 2023 | 13 | |
| 15 | 2014 | 13 | |
| 16 | 2020 | 12 | |
| 17 | 2024 | 11 | |
| 18 | 2012 | 11 | |
| 19 | 2010 | 11 | |
| 20 | 2013 | 10 |
About Thi-Thao Tran
Thi-Thao Tran is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Oncology and Industrial and Manufacturing Engineering, having authored 76 papers that have together received 630 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (26 papers), Advanced Neural Network Applications (25 papers), AI in cancer detection (20 papers), Radiomics and Machine Learning in Medical Imaging (10 papers), Cutaneous Melanoma Detection and Management (9 papers), Industrial Vision Systems and Defect Detection (9 papers), Machine Fault Diagnosis Techniques (8 papers) and Image Retrieval and Classification Techniques (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (311 citations), Otorhinolaryngology (42 citations), Media Technology (64 citations), Neurology (45 citations) and Radiology, Nuclear Medicine and Imaging (108 citations). Thi-Thao Tran has collaborated with scholars based in Vietnam, Taiwan and China. Frequent co-authors include Van-Truong Pham, Kuo‐Kai Shyu, Men‐Tzung Lo, Pa‐Chun Wang, Po‐Lei Lee, Chen Lin, Lian‐Yu Lin, Mao‐Yuan Su, Yung-Hung Wang and Wen‐Yih Isaac Tseng. Their work appears in journals such as Machine Vision and Applications, Biomedical Signal Processing and Control, Nonlinear Dynamics, Journal of Cardiology and Cognitive Computation.
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.