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2019 4
2020 6
2021 5
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13 results
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The Utility of Deep Learning in Breast Ultrasonic Imaging: A Review.
Fujioka T, Mori M, Kubota K, Oyama J, Yamaga E, Yashima Y, Katsuta L, Nomura K, Nara M, Oda G, Nakagawa T, Kitazume Y, Tateishi U. Fujioka T, et al. Among authors: katsuta l. Diagnostics (Basel). 2020 Dec 6;10(12):1055. doi: 10.3390/diagnostics10121055. Diagnostics (Basel). 2020. PMID: 33291266 Free PMC article. Review.
Feasibility of new fat suppression for breast MRI using pix2pix.
Mori M, Fujioka T, Katsuta L, Kikuchi Y, Oda G, Nakagawa T, Kitazume Y, Kubota K, Tateishi U. Mori M, et al. Among authors: katsuta l. Jpn J Radiol. 2020 Nov;38(11):1075-1081. doi: 10.1007/s11604-020-01012-5. Epub 2020 Jul 1. Jpn J Radiol. 2020. PMID: 32613357
Deep-learning approach with convolutional neural network for classification of maximum intensity projections of dynamic contrast-enhanced breast magnetic resonance imaging.
Fujioka T, Yashima Y, Oyama J, Mori M, Kubota K, Katsuta L, Kimura K, Yamaga E, Oda G, Nakagawa T, Kitazume Y, Tateishi U. Fujioka T, et al. Among authors: katsuta l. Magn Reson Imaging. 2021 Jan;75:1-8. doi: 10.1016/j.mri.2020.10.003. Epub 2020 Oct 10. Magn Reson Imaging. 2021. PMID: 33045323
Investigating the Image Quality and Utility of Synthetic MRI in the Breast.
Fujioka T, Mori M, Oyama J, Kubota K, Yamaga E, Yashima Y, Katsuta L, Nomura K, Nara M, Oda G, Nakagawa T, Tateishi U. Fujioka T, et al. Among authors: katsuta l. Magn Reson Med Sci. 2021 Feb 2. doi: 10.2463/mrms.mp.2020-0132. Online ahead of print. Magn Reson Med Sci. 2021. PMID: 33536401 Free article.
13 results