Hirofumi Kuno

1.0k total citations
48 papers, 649 citations indexed

About

Hirofumi Kuno is a scholar working on Surgery, Oncology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Hirofumi Kuno has authored 48 papers receiving a total of 649 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Surgery, 17 papers in Oncology and 17 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Hirofumi Kuno's work include Head and Neck Cancer Studies (15 papers), Salivary Gland Tumors Diagnosis and Treatment (10 papers) and Radiomics and Machine Learning in Medical Imaging (9 papers). Hirofumi Kuno is often cited by papers focused on Head and Neck Cancer Studies (15 papers), Salivary Gland Tumors Diagnosis and Treatment (10 papers) and Radiomics and Machine Learning in Medical Imaging (9 papers). Hirofumi Kuno collaborates with scholars based in Japan, United States and Norway. Hirofumi Kuno's co-authors include Osamu Sakai, Muhammad M. Qureshi, Baojun Li, Karen Buch, Satoshi Fujii, Katharina Otani, Margaret N. Chapman, Tatsushi Kobayashi, Kotaro Sekiya and Ryuichi Hayashi and has published in prestigious journals such as Journal of Clinical Oncology, Radiology and Annals of Oncology.

In The Last Decade

Hirofumi Kuno

41 papers receiving 645 citations

Peers

Hirofumi Kuno
Masayoshi Miyazaki Japan
Gerda M. Verduijn Netherlands
Sonja Stieb Switzerland
Y Kawashima Japan
D. Ciardo Italy
Philippe Henrot France
Tatsuya Nakamura Japan
Anthony Ciarallo Canada
Margaret N. Chapman United States
Marco Cianchetti Italy
Masayoshi Miyazaki Japan
Hirofumi Kuno
Citations per year, relative to Hirofumi Kuno Hirofumi Kuno (= 1×) peers Masayoshi Miyazaki

Countries citing papers authored by Hirofumi Kuno

Since Specialization
Citations

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

Fields of papers citing papers by Hirofumi Kuno

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hirofumi Kuno

This figure shows the co-authorship network connecting the top 25 collaborators of Hirofumi Kuno. A scholar is included among the top collaborators of Hirofumi Kuno 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 Hirofumi Kuno. Hirofumi Kuno 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.
Sasaki, Tomoaki, Hirofumi Kuno, Keiichi Nomura, et al.. (2025). CZT-based photon-counting-detector CT with deep-learning reconstruction: image quality and diagnostic confidence for lung tumor assessment. Japanese Journal of Radiology. 43(7). 1132–1144.
2.
Sasaki, Tomoaki, Hirofumi Kuno, Takashi Hiyama, et al.. (2024). Potential of spectral imaging generated by contrast-enhanced dual-energy CT for lung cancer histopathological classification – A preliminary study. European Journal of Radiology Open. 14. 100628–100628.
3.
Hiyama, Takashi, et al.. (2024). Imaging of the skull base and orbital tumors. Japanese Journal of Radiology. 43(2). 152–163.
4.
Sasaki, Tomoaki, Hirofumi Kuno, Takashi Hiyama, et al.. (2024). 2021 WHO Classification of Lung Cancer: Molecular Biology Research and Radiologic-Pathologic Correlation. Radiographics. 44(3). e230136–e230136. 5 indexed citations
5.
Nishimura, Bungo, et al.. (2023). Imaging of diffuse fibroepithelial polyps on surgical free flap in oral cancer patients: two case reports. Neuroradiology. 65(4). 815–818. 2 indexed citations
6.
7.
Okumura, Masayuki, Hidehiro Hojo, Masaki Nakamura, et al.. (2021). Radiation pneumonitis after palliative radiotherapy in cancer patients with interstitial lung disease. Radiotherapy and Oncology. 161. 47–54. 8 indexed citations
8.
9.
Hiyama, Takashi, et al.. (2021). A case of Epstein–Barr virus-positive mucocutaneous ulcer of the hypopharynx: a mimicker of hypopharyngeal squamous cell carcinoma. International Cancer Conference Journal. 11(1). 71–74. 1 indexed citations
10.
Hiyama, Takashi, Hirofumi Kuno, Kensaku Mori, et al.. (2020). Thoracic abnormal air collections in patients in the intensive care unit: radiograph findings correlated with CT. Insights into Imaging. 11(1). 35–35. 10 indexed citations
11.
Okumura, Masayuki, Atsushi Motegi, Sadamoto Zenda, et al.. (2020). Efficacy and safety of accelerated fractionated radiotherapy without elective nodal irradiation for T3N0 glottic cancer without vocal cord fixation. Head & Neck. 42(8). 1775–1782. 4 indexed citations
12.
Hiyama, Takashi, Hirofumi Kuno, Kotaro Sekiya, et al.. (2020). Extra-nodal extension in head and neck cancer: how radiologists can help staging and treatment planning. Japanese Journal of Radiology. 38(6). 489–506. 13 indexed citations
13.
Hiyama, Takashi, Kotaro Sekiya, Hirofumi Kuno, et al.. (2019). Imaging of extracranial head and neck lesions in cancer patients: a symptom-based approach. Japanese Journal of Radiology. 37(5). 354–370. 4 indexed citations
14.
Hiyama, Takashi, Hirofumi Kuno, Kotaro Sekiya, et al.. (2018). Bone Subtraction Iodine Imaging Using Area Detector CT for Evaluation of Skull Base Invasion by Nasopharyngeal Carcinoma. American Journal of Neuroradiology. 40(1). 135–141. 13 indexed citations
15.
Buch, Karen, Akifumi Fujita, Muhammad M. Qureshi, et al.. (2018). Using CT texture analysis to differentiate between nasopharyngeal carcinoma and age-matched adenoid controls. European Journal of Radiology. 108. 208–214. 11 indexed citations
16.
Kuno, Hirofumi, Kotaro Sekiya, Margaret N. Chapman, & Osamu Sakai. (2017). Miscellaneous and Emerging Applications of Dual-Energy Computed Tomography for the Evaluation of Intracranial Pathology. Neuroimaging Clinics of North America. 27(3). 411–427. 10 indexed citations
17.
Kuno, Hirofumi, Muhammad M. Qureshi, Margaret N. Chapman, et al.. (2017). CT Texture Analysis Potentially Predicts Local Failure in Head and Neck Squamous Cell Carcinoma Treated with Chemoradiotherapy. American Journal of Neuroradiology. 38(12). 2334–2340. 70 indexed citations
18.
Bando, Hideaki, Toshihiko Doi, Kei Muro, et al.. (2016). A multicenter phase II study of TAS-102 monotherapy in patients with pre-treated advanced gastric cancer (EPOC1201). European Journal of Cancer. 62. 46–53. 34 indexed citations
19.
Kuno, Hirofumi, Hiroaki Onaya, Satoshi Fujii, et al.. (2013). Primary staging of laryngeal and hypopharyngeal cancer: CT, MR imaging and dual-energy CT. European Journal of Radiology. 83(1). e23–e35. 49 indexed citations
20.
Ban, Daisuke, Seiichiro Yamamoto, Hirofumi Kuno, et al.. (2008). A Case of Huge Colon Carcinoma and Right Renal Angiomyolipoma Accompanied by Proximal Deep Venous Thrombosis, Pulmonary Embolism and Tumor Thrombus in the Renal Vein. Japanese Journal of Clinical Oncology. 38(10). 710–714. 9 indexed citations

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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