Shunya Sunami

631 total citations
18 papers, 512 citations indexed

About

Shunya Sunami is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Surgery. According to data from OpenAlex, Shunya Sunami has authored 18 papers receiving a total of 512 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Pulmonary and Respiratory Medicine, 8 papers in Radiology, Nuclear Medicine and Imaging and 4 papers in Surgery. Recurrent topics in Shunya Sunami's work include Radiomics and Machine Learning in Medical Imaging (5 papers), MRI in cancer diagnosis (5 papers) and Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (3 papers). Shunya Sunami is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (5 papers), MRI in cancer diagnosis (5 papers) and Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (3 papers). Shunya Sunami collaborates with scholars based in Japan. Shunya Sunami's co-authors include Hidetake Yabuuchi, Takeshi Kamitani, Hiroshi Honda, Yoshio Matsuo, Masamitsu Hatakenaka, Shuji Sakai, Taro Setoguchi, Kei Nishikawa, Yoshiyuki Shioyama and Hidetaka Yamamoto and has published in prestigious journals such as SHILAP Revista de lepidopterología, Radiology and International Journal of Radiation Oncology*Biology*Physics.

In The Last Decade

Shunya Sunami

16 papers receiving 506 citations

Peers

Shunya Sunami
Yasuaki Kuginuki Japan
Kuruva Manohar India
Jens Maus Germany
Lutz Freudenberg Germany
Alessia Farneti Italy
Luke Bonello Italy
Victor L. S. deCarvalho United States
Alexandr Lougovski Germany
I. Roebben Belgium
Cédric Desmonts France
Yasuaki Kuginuki Japan
Shunya Sunami
Citations per year, relative to Shunya Sunami Shunya Sunami (= 1×) peers Yasuaki Kuginuki

Countries citing papers authored by Shunya Sunami

Since Specialization
Citations

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

Fields of papers citing papers by Shunya Sunami

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shunya Sunami

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

All Works

18 of 18 papers shown
1.
Watanabe, Yusuke, Hiromichi Nakayama, Yoshitaka Gotoh, et al.. (2022). Intracholecystic papillary neoplasm associated with invasive carcinoma of the remnant gallbladder after subtotal cholecystectomy: a case report. SHILAP Revista de lepidopterología. 8(1). 31–31. 7 indexed citations
2.
Tanaka, Kentaro, Shunya Sunami, Takashige Maeyama, et al.. (2018). Durable response to nivolumab in a lung adenocarcinoma patient with idiopathic pulmonary fibrosis. Thoracic Cancer. 9(11). 1519–1521. 17 indexed citations
3.
Yabuuchi, Hidetake, Yoshio Matsuo, Koichiro Abe, et al.. (2015). Anterior mediastinal solid tumours in adults: characterisation using dynamic contrast-enhanced MRI, diffusion-weighted MRI, and FDG-PET/CT. Clinical Radiology. 70(11). 1289–1298. 44 indexed citations
4.
5.
Yano, Yuki, Hidetake Yabuuchi, Nobukazu Tanaka, et al.. (2013). Detectability of simulated pulmonary nodules on chest radiographs: Comparison between irradiation side sampling indirect flat-panel detector and computed radiography. European Journal of Radiology. 82(11). 2050–2054. 5 indexed citations
6.
Nagao, Michinobu, Yoshio Matsuo, Shunya Sunami, et al.. (2013). Detection of ground-glass opacities by use of hybrid iterative reconstruction (iDose) and low-dose 256-section computed tomography: a phantom study. Radiological Physics and Technology. 6(2). 299–304. 17 indexed citations
7.
Yabuuchi, Hidetake, Yoshio Matsuo, Hiroshi Tsukamoto, et al.. (2011). Correlation between pretreatment or follow-up CT findings and therapeutic effect of autologous peripheral blood stem cell transplantation for interstitial pneumonia associated with systemic sclerosis. European Journal of Radiology. 79(2). e74–e79. 7 indexed citations
8.
Kamitani, Takeshi, Hidetake Yabuuchi, Yoshio Matsuo, et al.. (2011). Diagnostic performance in differentiation of breast lesion on digital mammograms: comparison among hard-copy film, 3-megapixel LCD monitor, and 5-megapixel LCD monitor. Clinical Imaging. 35(5). 341–345. 7 indexed citations
9.
Yabuuchi, Hidetake, Masamitsu Hatakenaka, Koichi Takayama, et al.. (2011). Non–Small Cell Lung Cancer: Detection of Early Response to Chemotherapy by Using Contrast-enhanced Dynamic and Diffusion-weighted MR Imaging. Radiology. 261(2). 598–604. 87 indexed citations
10.
Hatakenaka, Masamitsu, Hidetake Yabuuchi, Yoshio Matsuo, et al.. (2011). A case of localized amyloidosis in the mediastinum, CT, MRI, and 18F-FDG-PET/CT findings. European Journal of Radiology Extra. 77(2). e39–e42.
11.
Hatakenaka, Masamitsu, Yoshiyuki Shioyama, Kenji Nakamura, et al.. (2011). Apparent Diffusion Coefficient Calculated with Relatively High b-Values Correlates with Local Failure of Head and Neck Squamous Cell Carcinoma Treated with Radiotherapy. American Journal of Neuroradiology. 32(10). 1904–1910. 50 indexed citations
12.
Kuroiwa, Toshiro, Shunya Sunami, Junji Murakami, et al.. (2011). Diffusion-weighted imaging (b value = 1500 s/mm2) is useful to decrease false-positive breast cancer cases due to fibrocystic changes. Breast Cancer. 20(2). 137–144. 25 indexed citations
13.
Kamitani, Takeshi, Yoshio Matsuo, Masamitsu Hatakenaka, et al.. (2011). Exogenous Lipoid Pneumonia Induced by Aspiration of Insecticide. Journal of Thoracic Imaging. 27(1). W18–W20. 5 indexed citations
14.
Hatakenaka, Masamitsu, Hidetake Yabuuchi, Shunya Sunami, et al.. (2010). Joint Position Affects Muscle Proton Diffusion: Evaluation With a 3-T MR System. American Journal of Roentgenology. 194(2). W208–W211. 13 indexed citations
15.
16.
Hatakenaka, Masamitsu, Katsumasa Nakamura, Hidetake Yabuuchi, et al.. (2010). Pretreatment Apparent Diffusion Coefficient of the Primary Lesion Correlates With Local Failure in Head-and-Neck Cancer Treated With Chemoradiotherapy or Radiotherapy. International Journal of Radiation Oncology*Biology*Physics. 81(2). 339–345. 90 indexed citations
17.
Hatakenaka, Masamitsu, Kenji Nakamura, Hidetake Yabuuchi, et al.. (2010). Pretreatment ADC of the Primary Lesion Correlates with Local Failure in Head and Neck Cancer Treated with Chemoradiotherapy or Radiotherapy. International Journal of Radiation Oncology*Biology*Physics. 78(3). S445–S446. 1 indexed citations
18.
Sunami, Shunya, Hiroyuki Irié, Hiroshi Honda, et al.. (1997). Diagnosis of hepatic angiomyolipomas; Comparison of US, CT and MR imaging. 42(5). 599–604.

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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