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863 results

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Page 1
Automated Interstitial Lung Abnormality Probability Prediction at CT: A Stepwise Machine Learning Approach in the Boston Lung Cancer Study.
Hata A, Aoyagi K, Hino T, Kawagishi M, Wada N, Song J, Wang X, Valtchinov VI, Nishino M, Muraguchi Y, Nakatsugawa M, Koga A, Sugihara N, Ozaki M, Hunninghake GM, Tomiyama N, Li Y, Christiani DC, Hatabu H. Hata A, et al. Among authors: aoyagi k. Radiology. 2024 Sep;312(3):e233435. doi: 10.1148/radiol.233435. Radiology. 2024. PMID: 39225600 Free PMC article.
Three-way Comparison of Whole-Body MR, Coregistered Whole-Body FDG PET/MR, and Integrated Whole-Body FDG PET/CT Imaging: TNM and Stage Assessment Capability for Non-Small Cell Lung Cancer Patients.
Ohno Y, Koyama H, Yoshikawa T, Takenaka D, Seki S, Yui M, Yamagata H, Aoyagi K, Matsumoto S, Sugimura K. Ohno Y, et al. Among authors: aoyagi k. Radiology. 2015 Jun;275(3):849-61. doi: 10.1148/radiol.14140936. Epub 2015 Jan 14. Radiology. 2015. PMID: 25584709
Comparative evaluation of newly developed model-based and commercially available hybrid-type iterative reconstruction methods and filter back projection method in terms of accuracy of computer-aided volumetry (CADv) for low-dose CT protocols in phantom study.
Ohno Y, Yaguchi A, Okazaki T, Aoyagi K, Yamagata H, Sugihara N, Koyama H, Yoshikawa T, Sugimura K. Ohno Y, et al. Among authors: aoyagi k. Eur J Radiol. 2016 Aug;85(8):1375-82. doi: 10.1016/j.ejrad.2016.05.001. Epub 2016 May 13. Eur J Radiol. 2016. PMID: 27423675
Machine learning for lung texture analysis on thin-section CT: Capability for assessments of disease severity and therapeutic effect for connective tissue disease patients in comparison with expert panel evaluations.
Ohno Y, Aoyagi K, Takenaka D, Yoshikawa T, Fujisawa Y, Sugihara N, Hamabuchi N, Hanamatsu S, Obama Y, Ueda T, Hattori H, Murayama K, Toyama H. Ohno Y, et al. Among authors: aoyagi k. Acta Radiol. 2022 Oct;63(10):1363-1373. doi: 10.1177/02841851211044973. Epub 2021 Oct 12. Acta Radiol. 2022. PMID: 34636644
Newly developed artificial intelligence algorithm for COVID-19 pneumonia: utility of quantitative CT texture analysis for prediction of favipiravir treatment effect.
Ohno Y, Aoyagi K, Arakita K, Doi Y, Kondo M, Banno S, Kasahara K, Ogawa T, Kato H, Hase R, Kashizaki F, Nishi K, Kamio T, Mitamura K, Ikeda N, Nakagawa A, Fujisawa Y, Taniguchi A, Ikeda H, Hattori H, Murayama K, Toyama H. Ohno Y, et al. Among authors: aoyagi k. Jpn J Radiol. 2022 Aug;40(8):800-813. doi: 10.1007/s11604-022-01270-5. Epub 2022 Apr 9. Jpn J Radiol. 2022. PMID: 35396667 Free PMC article. Clinical Trial.
Machine learning-based computer-aided simple triage (CAST) for COVID-19 pneumonia as compared with triage by board-certified chest radiologists.
Ohno Y, Aoki T, Endo M, Koyama H, Moriya H, Okada F, Higashino T, Sato H, Oyama-Manabe N, Haraguchi T, Arakita K, Aoyagi K, Ikeda Y, Kaminaga S, Taniguchi A, Sugihara N. Ohno Y, et al. Among authors: aoyagi k. Jpn J Radiol. 2024 Mar;42(3):276-290. doi: 10.1007/s11604-023-01495-y. Epub 2023 Oct 20. Jpn J Radiol. 2024. PMID: 37861955 Free PMC article.
Automated chest CT three-dimensional quantification of body composition: adipose tissue and paravertebral muscle.
Hata A, Muraguchi Y, Nakatsugawa M, Wang X, Song J, Wada N, Hino T, Aoyagi K, Kawagishi M, Negishi T, Valtchinov VI, Nishino M, Koga A, Sugihara N, Ozaki M, Hunninghake GM, Tomiyama N, Schiebler ML, Li Y, Christiani DC, Hatabu H. Hata A, et al. Among authors: aoyagi k. Sci Rep. 2024 Dec 30;14(1):32117. doi: 10.1038/s41598-024-83897-0. Sci Rep. 2024. PMID: 39738489 Free PMC article.
863 results