Koji Takumi
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- MRI in cancer diagnosis 19
- Radiomics and Machine Learning in Medical Imaging 17
- Advanced MRI Techniques and Applications 7
- Advanced Neuroimaging Techniques and Applications 5
- Hepatology top 5%
- Hepatocellular Carcinoma Treatment and Prognosis 6
- Oncology top 10%
- Pancreatic and Hepatic Oncology Research 12
- Otorhinolaryngology top 10%
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- Advanced X-ray and CT Imaging 7
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- Adrenal and Paraganglionic Tumors 5
- Co-authors
- Yoshihiko FukukuraKiyohisa KamimuraTakashi YoshiuraYuichi KumagaeMasayuki NakajoTomohide YoneyamaHiroto HakamadaMasanori Nakajo
- Journals
- SHILAP Revista de lepidopterología (1 paper)Scientific Reports (2 papers)Radiology (2 papers)
- Partner nations
- JapanUnited StatesGermany
In The Last Decade
Koji Takumi
59 papers receiving 925 citations
Peers
Comparison fields: 5 of 63
- Radiology, Nuclear Medicine and Imaging 526
- Hepatology 132
- Oncology 295
- Otorhinolaryngology 43
- Epidemiology 243
Countries citing papers authored by Koji Takumi
This map shows the geographic impact of Koji Takumi'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 Koji Takumi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Koji Takumi more than expected).
Fields of papers citing papers by Koji Takumi
This network shows the impact of papers produced by Koji Takumi. 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 Koji Takumi. The network helps show where Koji Takumi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Koji Takumi, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 0 | |
| 5 | 2025 | 0 | |
| 6 | 2024 | 0 | |
| 7 | 2024 | 3 | |
| 8 | 2024 | 3 | |
| 9 | 2024 | 6 | |
| 10 | 2024 | 2 | |
| 11 | 2024 | 2 | |
| 12 | 2022 | 8 | |
| 13 | 2019 | 10 | |
| 14 | 2019 | 5 | |
| 15 | 2018 | 41 | |
| 16 | 2016 | 41 | |
| 17 | 2015 | 74 | |
| 18 | 2014 | 46 | |
| 19 | 2013 | 4 | |
| 20 | 2011 | 8 |
About Koji Takumi
Koji Takumi is a scholar working on Radiology, Nuclear Medicine and Imaging, Otorhinolaryngology and Hepatology, having authored 70 papers that have together received 934 indexed citations. Recurring topics across this work include MRI in cancer diagnosis (19 papers), Radiomics and Machine Learning in Medical Imaging (17 papers), Pancreatic and Hepatic Oncology Research (12 papers), Advanced X-ray and CT Imaging (7 papers), Advanced MRI Techniques and Applications (7 papers), Hepatocellular Carcinoma Treatment and Prognosis (6 papers), Adrenal and Paraganglionic Tumors (5 papers) and Advanced Neuroimaging Techniques and Applications (5 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (526 citations), Hepatology (132 citations) and Oncology (295 citations). Koji Takumi has collaborated with scholars based in Japan, United States and Germany. Frequent co-authors include Yoshihiko Fukukura, Kiyohisa Kamimura, Takashi Yoshiura, Yuichi Kumagae, Masayuki Nakajo, Tomohide Yoneyama, Hiroto Hakamada, Masanori Nakajo, Michiyo Higashi and Hiroaki Nagano. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and 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.