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Combined Use of Texture Features and Morphological Classification Based on Dynamic Contrast-enhanced MR Imaging: Differentiating Benign and Malignant Breast Masses with High Negative Predictive Value.
Ohyu S, Tozaki M, Sasaki M, Chiba H, Xiao Q, Fujisawa Y, Sagara Y. Ohyu S, et al. Among authors: fujisawa y. Magn Reson Med Sci. 2022 Jul 1;21(3):485-498. doi: 10.2463/mrms.mp.2020-0160. Epub 2021 Jun 26. Magn Reson Med Sci. 2022. PMID: 34176860 Free PMC article.
Dynamic Contrast-enhanced Area-detector CT vs Dynamic Contrast-enhanced Perfusion MRI vs FDG-PET/CT: Comparison of Utility for Quantitative Therapeutic Outcome Prediction for NSCLC Patients Undergoing Chemoradiotherapy.
Seki S, Fujisawa Y, Yui M, Kishida Y, Koyama H, Ohyu S, Sugihara N, Yoshikawa T, Ohno Y. Seki S, et al. Among authors: fujisawa y. Magn Reson Med Sci. 2020 Feb 10;19(1):29-39. doi: 10.2463/mrms.mp.2018-0158. Epub 2019 Mar 18. Magn Reson Med Sci. 2020. PMID: 30880291 Free PMC article.
Dynamic contrast-enhanced perfusion area detector CT for non-small cell lung cancer patients: Influence of mathematical models on early prediction capabilities for treatment response and recurrence after chemoradiotherapy.
Ohno Y, Koyama H, Fujisawa Y, Yoshikawa T, Seki S, Sugihara N, Sugimura K. Ohno Y, et al. Among authors: fujisawa y. Eur J Radiol. 2016 Jan;85(1):176-186. doi: 10.1016/j.ejrad.2015.11.009. Epub 2015 Nov 10. Eur J Radiol. 2016. PMID: 26724663
Hybrid Type iterative reconstruction method vs. filter back projection method: Capability for radiation dose reduction and perfusion assessment on dynamic first-pass contrast-enhanced perfusion chest area-detector CT.
Ohno Y, Koyama H, Fujisawa Y, Yoshikawa T, Inokawa H, Sugihara N, Seki S, Sugimura K. Ohno Y, et al. Among authors: fujisawa y. Eur J Radiol. 2016 Jan;85(1):164-175. doi: 10.1016/j.ejrad.2015.11.010. Epub 2015 Nov 11. Eur J Radiol. 2016. PMID: 26724662
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: fujisawa y. Acta Radiol. 2022 Oct;63(10):1363-1373. doi: 10.1177/02841851211044973. Epub 2021 Oct 12. Acta Radiol. 2022. PMID: 34636644
887 results