Tae Iwasawa

4.2k total citations
187 papers, 2.5k citations indexed

About

Tae Iwasawa is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Physiology. According to data from OpenAlex, Tae Iwasawa has authored 187 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 120 papers in Pulmonary and Respiratory Medicine, 57 papers in Radiology, Nuclear Medicine and Imaging and 26 papers in Physiology. Recurrent topics in Tae Iwasawa's work include Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (88 papers), Advanced MRI Techniques and Applications (34 papers) and Lung Cancer Treatments and Mutations (23 papers). Tae Iwasawa is often cited by papers focused on Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (88 papers), Advanced MRI Techniques and Applications (34 papers) and Lung Cancer Treatments and Mutations (23 papers). Tae Iwasawa collaborates with scholars based in Japan, Brazil and Mozambique. Tae Iwasawa's co-authors include Takashi Ogura, Tomohisa Baba, Tamiko Takemura, Eri Hagiwara, Toshiyuki Gotoh, Koji Okudela, Hideya Kitamura, Akimasa Sekine, Takashi Ogura and Shingo Kato and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Journal of the American College of Cardiology.

In The Last Decade

Tae Iwasawa

172 papers receiving 2.5k citations

Peers

Tae Iwasawa

PRM

RNMI

PHYSI

CCM

ONCOL

Marcus Both Germany

Ashkan A. Malayeri United States

Chiho Ohbayashi Japan

Robert Lisbona Canada

Kazuyoshi Suga Japan

Ehab M. Kamel Switzerland

Felix Nensa Germany

Philipp Heusch Germany

Yuichiro Maruyama Japan

Katrien Grünberg Netherlands

Marcus Both Germany

Tae Iwasawa

1.5k ×1.0

PRM

552 ×0.9

RNMI

477 ×1.1

PHYSI

152 ×0.5

CCM

226 ×0.7

ONCOL

Citations per year, relative to Tae Iwasawa Tae Iwasawa (= 1×) peers Marcus Both

Countries citing papers authored by Tae Iwasawa

Since Specialization

Citations

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

Fields of papers citing papers by Tae Iwasawa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tae Iwasawa

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

All Works

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20 of 20 papers shown

Ito, Kenichi, Shingo Kato, Kazuki Fukui, et al.. (2025). Integrating CT-Based Lung Fibrosis and MRI-Derived Right Ventricular Function for the Detection of Pulmonary Hypertension in Interstitial Lung Disease. Journal of Clinical Medicine. 14(15). 5329–5329.

Okuda, Ryo, et al.. (2025). Antifibrotic agents in progressive pulmonary fibrosis and non-progressive pulmonary fibrosis of fibrotic hypersensitivity pneumonitis. Respiratory Investigation. 63(5). 737–743.

Yamamoto, Akira, Takao Hiraki, Yoshitaka Tamura, et al.. (2024). Radiofrequency Ablation in Patients with Interstitial Lung Disease and Lung Neoplasm: A Retrospective Multicenter Study. Journal of Vascular and Interventional Radiology. 35(9). 1305–1312.

Iwasawa, Tae, Toshihiro Misumi, Koji Okudela, et al.. (2024). Correlation of CT-based radiomics analysis with pathological cellular infiltration in fibrosing interstitial lung diseases. Japanese Journal of Radiology. 42(10). 1157–1167. 4 indexed citations

Iwasawa, Tae, Tomohisa Baba, Toshihiro Misumi, et al.. (2024). Evaluation of Progressive Architectural Distortion in Idiopathic Pulmonary Fibrosis Using Deformable Registration of Sequential CT Images. Diagnostics. 14(15). 1650–1650.

Handa, Tomohiro, Shoko Matsui, Hiroshi Yamamoto, et al.. (2023). The 2022 revised diagnostic criteria for IgG4-related respiratory diseases. Respiratory Investigation. 61(6). 755–759.

Iwasawa, Tae, et al.. (2023). Quantitative Analysis for Lung Disease on Thin-Section CT. Diagnostics. 13(18). 2988–2988. 5 indexed citations

Iwasawa, Tae, Tsuneo Yamashiro, Daisuke Utsunomiya, et al.. (2022). Effects of Automatic Deep-Learning-Based Lung Analysis on Quantification of Interstitial Lung Disease: Correlation with Pulmonary Function Test Results and Prognosis. Diagnostics. 12(12). 3038–3038. 13 indexed citations

Muto, Yutaka, Akimasa Sekine, Eri Hagiwara, et al.. (2022). Clinical characteristics of pulmonary hypertension in patients with pleuroparenchymal fibroelastosis. Respiratory Investigation. 60(4). 543–550. 4 indexed citations

10.

Iwasawa, Tae, et al.. (2021). Pulmonary vascular enlargement and lesion extent on computed tomography are correlated with COVID-19 disease severity. Japanese Journal of Radiology. 39(5). 451–458. 18 indexed citations

11.

Kato, Shingo, et al.. (2021). Imaging of COVID-19: An update of current evidences. Diagnostic and Interventional Imaging. 102(9). 493–500. 14 indexed citations

12.

Iwasawa, Tae, Takashi Ogura, Tsuneo Yamashiro, et al.. (2020). Pulmonary flow assessment by phase-contrast MRI can predict short-term mortality of fibrosing interstitial lung diseases. Acta Radiologica. 61(10). 1350–1358.

13.

Saito, Yoshinobu, Shinichi Sasaki, Junya Tominaga, et al.. (2020). Radiographic features and poor prognostic factors of interstitial lung disease with nivolumab for non–small cell lung cancer. Cancer Science. 112(4). 1495–1505. 10 indexed citations

14.

Sata, Masafumi, Shinichi Sasaki, Yoshinobu Saito, et al.. (2020). Treatment and relapse of interstitial lung disease in nivolumab‐treated patients with non–small cell lung cancer. Cancer Science. 112(4). 1506–1513. 9 indexed citations

15.

Fujita, Ryo, Tae Iwasawa, Takatoshi Aoki, et al.. (2020). Detection of the usual interstitial pneumonia pattern in chest CT: effect of computer-aided diagnosis on radiologist diagnostic performance. Acta Radiologica. 65(3). 259–266. 2 indexed citations

16.

Iwasawa, Tae, Koji Okudela, Tamiko Takemura, et al.. (2019). Computer-aided Quantification of Pulmonary Fibrosis in Patients with Lung Cancer: Relationship to Disease-free Survival. Radiology. 292(2). 489–498. 35 indexed citations

17.

Iwata, Takekazu, Ichiro Yoshino, Shigetoshi Yoshida, et al.. (2015). Effect of Perioperative Pirfenidone Treatment in Lung Cancer Patients With Idiopathic Pulmonary Fibrosis (West Japan Oncolgy Group 6711L): A Phase II Study. CHEST Journal. 148(4). 395A–395A. 1 indexed citations

18.

Iwasawa, Tae, et al.. (2012). Computer-aided segmentation system for 3D chest CT. 57(1). 41–47. 1 indexed citations

19.

Kagei, Seiichiro, et al.. (2011). Calibration of Gd-Contrast Agent and Perfusion Analysis for Sequential Lung MR Images. 35(8). 21–24. 1 indexed citations

20.

Asakura, Akira, et al.. (2004). Shape Tracking on Chest MR Sequence Images Using Respiratory Patterns. 33(6). 1115–1122. 10 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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