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Performance of Machine Learning Methods Based on Multi-Sequence Textural Parameters Using Magnetic Resonance Imaging and Clinical Information to Differentiate Malignant and Benign Soft Tissue Tumors.
Nakagawa M, Nakaura T, Yoshida N, Azuma M, Uetani H, Nagayama Y, Kidoh M, Miyamoto T, Yamashita Y, Hirai T. Nakagawa M, et al. Among authors: yoshida n. Acad Radiol. 2023 Jan;30(1):83-92. doi: 10.1016/j.acra.2022.04.007. Epub 2022 Jun 18. Acad Radiol. 2023. PMID: 35725692
Update on the Use of Artificial Intelligence in Hepatobiliary MR Imaging.
Nakaura T, Kobayashi N, Yoshida N, Shiraishi K, Uetani H, Nagayama Y, Kidoh M, Hirai T. Nakaura T, et al. Among authors: yoshida n. Magn Reson Med Sci. 2023 Apr 1;22(2):147-156. doi: 10.2463/mrms.rev.2022-0102. Epub 2023 Jan 26. Magn Reson Med Sci. 2023. PMID: 36697024 Free PMC article. Review.
Optimizing High-Resolution MR Angiography: The Synergistic Effects of 3D Wheel Sampling and Deep Learning-Based Reconstruction.
Sasaki G, Uetani H, Nakaura T, Nakahara K, Morita K, Nagayama Y, Kidoh M, Iwashita K, Yoshida N, Hokamura M, Yamashita Y, Nakajima M, Ueda M, Hirai T. Sasaki G, et al. Among authors: yoshida n. J Comput Assist Tomogr. 2024 Sep-Oct 01;48(5):819-825. doi: 10.1097/RCT.0000000000001590. Epub 2024 Feb 12. J Comput Assist Tomogr. 2024. PMID: 38346820
3,404 results