Junichi Tsuchiya

485 total citations
73 papers, 308 citations indexed

About

Junichi Tsuchiya is a scholar working on Radiology, Nuclear Medicine and Imaging, Surgery and Artificial Intelligence. According to data from OpenAlex, Junichi Tsuchiya has authored 73 papers receiving a total of 308 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Radiology, Nuclear Medicine and Imaging, 15 papers in Surgery and 12 papers in Artificial Intelligence. Recurrent topics in Junichi Tsuchiya's work include Medical Imaging Techniques and Applications (16 papers), Metaheuristic Optimization Algorithms Research (12 papers) and Radiomics and Machine Learning in Medical Imaging (10 papers). Junichi Tsuchiya is often cited by papers focused on Medical Imaging Techniques and Applications (16 papers), Metaheuristic Optimization Algorithms Research (12 papers) and Radiomics and Machine Learning in Medical Imaging (10 papers). Junichi Tsuchiya collaborates with scholars based in Japan, United States and China. Junichi Tsuchiya's co-authors include Ukihide Tateishi, Kota Yokoyama, Koichiro Kimura, Tomoyuki Fujioka, M. Mori, Emi Yamaga, Mitsuhiro Kishino, Tsuyoshi Nakagawa, Goshi Oda and G. Kimura and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and European Journal of Nuclear Medicine and Molecular Imaging.

In The Last Decade

Junichi Tsuchiya

58 papers receiving 301 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Junichi Tsuchiya Japan 10 158 58 45 45 43 73 308
Koichiro Kimura Japan 12 190 1.2× 128 2.2× 29 0.6× 82 1.8× 47 1.1× 56 398
Qingling Li China 11 79 0.5× 76 1.3× 92 2.0× 26 0.6× 74 1.7× 31 346
Antonio Notaristefano Italy 10 87 0.6× 84 1.4× 42 0.9× 23 0.5× 11 0.3× 32 333
Jiamin Liu China 10 202 1.3× 31 0.5× 50 1.1× 41 0.9× 144 3.3× 27 568
Gehad A. Saleh Egypt 11 160 1.0× 46 0.8× 44 1.0× 42 0.9× 30 0.7× 41 337
Seyed Masoud Rezaeijo Iran 17 406 2.6× 163 2.8× 62 1.4× 174 3.9× 110 2.6× 31 603
Nicola Altini Italy 12 153 1.0× 50 0.9× 37 0.8× 172 3.8× 50 1.2× 26 343
Bowen Xin China 11 224 1.4× 110 1.9× 76 1.7× 50 1.1× 58 1.3× 22 404
Mingxiang Wu China 12 216 1.4× 89 1.5× 30 0.7× 104 2.3× 43 1.0× 33 386

Countries citing papers authored by Junichi Tsuchiya

Since Specialization
Citations

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

Fields of papers citing papers by Junichi Tsuchiya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junichi Tsuchiya

This figure shows the co-authorship network connecting the top 25 collaborators of Junichi Tsuchiya. A scholar is included among the top collaborators of Junichi Tsuchiya 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 Junichi Tsuchiya. Junichi Tsuchiya is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Yokoyama, Kota, Mitsuru Matsuki, Kimiteru Ito, et al.. (2025). Advances in multimodal imaging for adrenal gland disorders: integrating CT, MRI, and nuclear medicine. Japanese Journal of Radiology. 43(6). 903–926.
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Kimura, Koichiro, Yusuke Kawasaki, Kenichi Fukui, et al.. (2024). Prospective evaluation of PI-RADSv2.1 using multiparametric and biparametric MRI for detecting clinically significant prostate cancer based on MRI/US fusion-guided biopsy. Japanese Journal of Radiology. 43(3). 472–482. 1 indexed citations
4.
Kimura, Koichiro, Tatsuya Yamamoto, Junichi Tsuchiya, et al.. (2024). A diagnostic approach of various urethral diseases using multimodal imaging findings: comprehensive overview. Abdominal Radiology. 49(12). 4416–4436.
5.
Yokoyama, Kota, et al.. (2024). Brain perfusion SPECT in dementia: what radiologists should know. Japanese Journal of Radiology. 42(11). 1215–1230. 4 indexed citations
6.
Aoki, Hikaru, Yasunari Miyazaki, Kota Yokoyama, et al.. (2023). Deep convolutional neural network for differentiating between sarcoidosis and lymphoma based on [18F]FDG maximum-intensity projection images. European Radiology. 34(1). 374–383. 9 indexed citations
7.
Mori, M., Tomoyuki Fujioka, Leona Katsuta, et al.. (2023). Deep Learning-Based Image Quality Improvement in Digital Positron Emission Tomography for Breast Cancer. Diagnostics. 13(4). 794–794. 2 indexed citations
8.
Kimura, Koichiro, Soichiro Yoshida, Junichi Tsuchiya, et al.. (2023). Novel utility of Vesical Imaging-Reporting and Data System in multimodal treatment for muscle-invasive bladder cancer. European Radiology. 33(9). 6245–6255. 2 indexed citations
9.
Yokoyama, Kota, et al.. (2023). [18F]-FDG PET/CT is useful for early detection of Stewart-Treves syndrome, in patients with chronic lymphedema. European Journal of Nuclear Medicine and Molecular Imaging. 50(9). 2916–2917.
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Yokoyama, Kota, Jun Oyama, Junichi Tsuchiya, et al.. (2022). Branch-like enhancement on contrast enhanced MRI is a specific finding of cerebellar lymphoma compared with other pathologies. Scientific Reports. 12(1). 3591–3591.
12.
Tateishi, Ukihide, et al.. (2021). Image quality and quantification accuracy dependence on patient body mass in 89Zr PET/CT imaging. EJNMMI Physics. 8(1). 72–72. 5 indexed citations
13.
Kimura, Koichiro, Soichiro Yoshida, Junichi Tsuchiya, et al.. (2021). Usefulness of texture features of apparent diffusion coefficient maps in predicting chemoradiotherapy response in muscle-invasive bladder cancer. European Radiology. 32(1). 671–679. 21 indexed citations
14.
Kitazume, Yoshio, Junichi Tsuchiya, K Takenaka, et al.. (2020). High b-value computed diffusion-weighted imaging for differentiating bowel inflammation in Crohn's disease. European Journal of Radiology. 133. 109362–109362. 2 indexed citations
15.
Fujioka, Tomoyuki, M. Mori, Junichi Tsuchiya, et al.. (2020). Late-onset pneumothorax in a COVID-19 patient treated with ventilation and ECMO: A case report and literature review. SHILAP Revista de lepidopterología. 15(12). 2560–2564. 7 indexed citations
16.
Oshima, Takumi, Junichi Tsuchiya, & Ukihide Tateishi. (2019). Efficacy of Single Energy Metal Artifact Reduction (SEMAR) for Head and Neck Cancer. 66(4). 59–64.
17.
Tsuchiya, Junichi, Daisuke Tezuka, Yasuhiro Maejima, et al.. (2019). Takayasu arteritis: clinical importance of extra-vessel uptake on FDG PET/CT. SHILAP Revista de lepidopterología. 3(1). 12–12. 2 indexed citations
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Maeda, Ichiro, Hirotaka Koizumi, Shinya Tajima, et al.. (2015). Comparison between Ki67 labeling index determined using image analysis software with virtual slide system and that determined visually in breast cancer. Breast Cancer. 23(5). 745–751. 21 indexed citations
20.
Tsuchiya, Junichi & Keiichiro Yasuda. (2010). Particle swarm optimization based integrative optimal design method for surface motor with multi-degree of freedom. World Automation Congress. 1–6.

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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