Nakamoto T - Search Results

1

Fast Statistical Iterative Reconstruction for Mega-voltage Computed Tomography.

Ozaki S, Haga A, Chao E, Maurer C, Nawa K, Ohta T, Nakamoto T, Nozawa Y, Magome T, Nakano M, Nakagawa K. Ozaki S, et al. Among authors: nakamoto t. J Med Invest. 2020;67(1.2):30-39. doi: 10.2152/jmi.67.30. J Med Invest. 2020. PMID: 32378615 Free article. Review.

2

Volumetric and dosimetric comparison of organs at risk between the prone and supine positions in postoperative radiotherapy for prostate cancer.

Sawayanagi S, Yamashita H, Ogita M, Kiritoshi T, Nakamoto T, Abe O, Nakagawa K. Sawayanagi S, et al. Among authors: nakamoto t. Radiat Oncol. 2018 Apr 17;13(1):70. doi: 10.1186/s13014-018-1023-0. Radiat Oncol. 2018. PMID: 29665832 Free PMC article.

3

Cone Beam Computed Tomography Image Quality Improvement Using a Deep Convolutional Neural Network.

Kida S, Nakamoto T, Nakano M, Nawa K, Haga A, Kotoku J, Yamashita H, Nakagawa K. Kida S, et al. Among authors: nakamoto t. Cureus. 2018 Apr 29;10(4):e2548. doi: 10.7759/cureus.2548. Cureus. 2018. PMID: 29963342 Free PMC article.

4

[An Introduction to Radiomics: Toward a New Era of Precision Medicine].

Nakamoto T, Haga A, Takahashi W. Nakamoto T, et al. Igaku Butsuri. 2018;38(3):129-134. doi: 10.11323/jjmp.38.3_129. Igaku Butsuri. 2018. PMID: 30584215 Free article. Review. Japanese.

5

Radiomics Analysis for Glioma Malignancy Evaluation Using Diffusion Kurtosis and Tensor Imaging.

Takahashi S, Takahashi W, Tanaka S, Haga A, Nakamoto T, Suzuki Y, Mukasa A, Takayanagi S, Kitagawa Y, Hana T, Nejo T, Nomura M, Nakagawa K, Saito N. Takahashi S, et al. Among authors: nakamoto t. Int J Radiat Oncol Biol Phys. 2019 Nov 15;105(4):784-791. doi: 10.1016/j.ijrobp.2019.07.011. Epub 2019 Jul 22. Int J Radiat Oncol Biol Phys. 2019. PMID: 31344432

6

Visual enhancement of Cone-beam CT by use of CycleGAN.

Kida S, Kaji S, Nawa K, Imae T, Nakamoto T, Ozaki S, Ohta T, Nozawa Y, Nakagawa K. Kida S, et al. Among authors: nakamoto t. Med Phys. 2020 Mar;47(3):998-1010. doi: 10.1002/mp.13963. Epub 2020 Jan 3. Med Phys. 2020. PMID: 31840269

7

Prediction of malignant glioma grades using contrast-enhanced T1-weighted and T2-weighted magnetic resonance images based on a radiomic analysis.

Nakamoto T, Takahashi W, Haga A, Takahashi S, Kiryu S, Nawa K, Ohta T, Ozaki S, Nozawa Y, Tanaka S, Mukasa A, Nakagawa K. Nakamoto T, et al. Sci Rep. 2019 Dec 19;9(1):19411. doi: 10.1038/s41598-019-55922-0. Sci Rep. 2019. PMID: 31857632 Free PMC article.

8

Publisher Correction: Prediction of malignant glioma grades using contrast-enhanced T1-weighted and T2-weighted magnetic resonance images based on a radiomic analysis.

Nakamoto T, Takahashi W, Haga A, Takahashi S, Kiryu S, Nawa K, Ohta T, Ozaki S, Nozawa Y, Tanaka S, Mukasa A, Nakagawa K. Nakamoto T, et al. Sci Rep. 2020 Feb 17;10(1):3073. doi: 10.1038/s41598-020-60086-3. Sci Rep. 2020. PMID: 32066815 Free PMC article.

9

[Improvement in Image Quality of CBCT during Treatment by Cycle Generative Adversarial Network].

Imae T, Kaji S, Kida S, Matsuda K, Takenaka S, Aoki A, Nakamoto T, Ozaki S, Nawa K, Yamashita H, Nakagawa K, Abe O. Imae T, et al. Among authors: nakamoto t. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2020;76(11):1173-1184. doi: 10.6009/jjrt.2020_JSRT_76.11.1173. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2020. PMID: 33229847 Free article. Japanese.

10

Training of deep cross-modality conversion models with a small data set, and their application in megavoltage CT to kilovoltage CT conversion.

Ozaki S, Kaji S, Nawa K, Imae T, Aoki A, Nakamoto T, Ohta T, Nozawa Y, Yamashita H, Haga A, Nakagawa K. Ozaki S, et al. Among authors: nakamoto t. Med Phys. 2022 Jun;49(6):3769-3782. doi: 10.1002/mp.15626. Epub 2022 Apr 17. Med Phys. 2022. PMID: 35315529

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