1. A multiparametric MRI-based machine learning to distinguish between uterine sarcoma and benign leiomyoma: comparison with 18F-FDG PET/CT. Issue 2 (February 2019) Authors: Nakagawa, M.; Nakaura, T.; Namimoto, T.; Iyama, Y.; Kidoh, M.; Hirata, K.; Nagayama, Y.; Oda, S.; Sakamoto, F.; Shiraishi, S.; Yamashita, Y. Journal: Clinical radiology Issue: Volume 74:Issue 2(2019) Page Start: 167.e1 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
2. Dual-layer detector CT of chest, abdomen, and pelvis with a one-third iodine dose: image quality, radiation dose, and optimal monoenergetic settings. Issue 12 (December 2018) Authors: Nagayama, Y.; Nakaura, T.; Oda, S.; Taguchi, N.; Utsunomiya, D.; Funama, Y.; Kidoh, M.; Namimoto, T.; Sakabe, D.; Hatemura, M.; Yamashita, Y. Journal: Clinical radiology Issue: Volume 73:Issue 12(2018) Page Start: 1058.e21 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
3. Virtual magnetic resonance lumbar spine images generated from computed tomography images using conditional generative adversarial networks. Issue 2 (May 2022) Authors: Gotoh, M.; Nakaura, T.; Funama, Y.; Morita, K.; Sakabe, D.; Uetani, H.; Nagayama, Y.; Kidoh, M.; Hatemura, M.; Masuda, T.; Hirai, T. Journal: Radiography Issue: Volume 28:Issue 2(2022) Page Start: 447 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗