Article Versions Notes

Urase Y, Nishio M, Ueno Y, Kono AK, Sofue K, Kanda T, Maeda T, Nogami M, Hori M, Murakami T. Simulation Study of Low-Dose Sparse-Sampling CT with Deep Learning-Based Reconstruction: Usefulness for Evaluation of Ovarian Cancer Metastasis. Applied Sciences. 2020; 10(13):4446. https://doi.org/10.3390/app10134446

Urase, Yasuyo, Mizuho Nishio, Yoshiko Ueno, Atsushi K. Kono, Keitaro Sofue, Tomonori Kanda, Takaki Maeda, Munenobu Nogami, Masatoshi Hori, and Takamichi Murakami. 2020. "Simulation Study of Low-Dose Sparse-Sampling CT with Deep Learning-Based Reconstruction: Usefulness for Evaluation of Ovarian Cancer Metastasis" Applied Sciences 10, no. 13: 4446. https://doi.org/10.3390/app10134446

Urase, Y., Nishio, M., Ueno, Y., Kono, A. K., Sofue, K., Kanda, T., Maeda, T., Nogami, M., Hori, M., & Murakami, T. (2020). Simulation Study of Low-Dose Sparse-Sampling CT with Deep Learning-Based Reconstruction: Usefulness for Evaluation of Ovarian Cancer Metastasis. Applied Sciences, 10(13), 4446. https://doi.org/10.3390/app10134446