YASUNORI NAGAYAMA

Affiliation and department：

Research field (1)： Radiology

Research theme for competitive and other funds (4)：

2024 - 2028 Multi-energy CTを用いた副腎腫瘍の非侵襲的な診断手法の確立
2023 - 2026 超解像技術を活用した小児CTの被ばく線量最適化
2021 - 2025 人工知能を用いて多層検出器CT画像より疑似的なMR画像を作成する研究
2019 - 2022 小児CTにおける深層学習画像再構成を用いた低被曝撮影法の開発

Papers (96)：

Yasunori Nagayama, Hidetaka Hayashi, Narumi Taguchi, Ryuya Yoshida, Ryota Harai, Masafumi Kidoh, Seitaro Oda, Takeshi Nakaura, Toshinori Hirai. Diagnostic performance of hepatic CT and chemical-shift MRI to discriminate lipid-poor adrenal adenomas from hepatocellular carcinoma metastases. Abdominal radiology (New York). 2024
Goh Sasaki, Hiroyuki Uetani, Takeshi Nakaura, Keiichi Nakahara, Kosuke Morita, Yasunori Nagayama, Masafumi Kidoh, Koya Iwashita, Naofumi Yoshida, Masamichi Hokamura, et al. Optimizing High-Resolution MR Angiography: The Synergistic Effects of 3D Wheel Sampling and Deep Learning-Based Reconstruction. Journal of Computer Assisted Tomography. 2024
Masamichi Hokamura, Hiroyuki Uetani, Takeshi Nakaura, Kensei Matsuo, Kosuke Morita, Yasunori Nagayama, Masafumi Kidoh, Yuichi Yamashita, Mitsuharu Ueda, Akitake Mukasa, et al. Exploring the impact of super-resolution deep learning on MR angiography image quality. Neuroradiology. 2023
Shinpei Yamaguchi, Seitaro Oda, Masafumi Kidoh, Hidetaka Hayashi, Seiji Takashio, Hiroki Usuku, Yasunori Nagayama, Takeshi Nakaura, Kenichi Tsujita, Toshinori Hirai, et al. Cardiac MRI T1 and T2 Mapping as a Quantitative Imaging Biomarker in Transthyretin Amyloid Cardiomyopathy. Academic radiology. 2023
Takeshi Nakaura, Naofumi Yoshida, Naoki Kobayashi, Kaori Shiraishi, Yasunori Nagayama, Hiroyuki Uetani, Masafumi Kidoh, Masamichi Hokamura, Yoshinori Funama, Toshinori Hirai. Preliminary assessment of automated radiology report generation with generative pre-trained transformers: comparing results to radiologist-generated reports. Japanese journal of radiology. 2023

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MISC (30)：

永山泰教. 特集1 令和にアップデートしたい膵癌の画像診断画像診断の進歩:CT-膵癌診療におけるdual-energy CTの有用性-. 臨床画像. 2023. 39. 7. 739-747
坂部大介, 船間芳憲, 永山泰教, 中戸研吾, 榎本隆文, 後藤淳, 羽手村昌宏. 血管模擬ファントムを用いた冠動脈CT-angiographyにおける超解像深層学習再構成の血管描出能の改善. 日本放射線技術学会総会学術大会予稿集. 2023. 79回. 163-163
永山泰教. (Session1)Canon高精細技術 DLRが可能とする低被ばくと高画質の両立. INNERVISION. 2022. 37. 11付録. 4-5
榎本隆文, 永山泰教, 坂部大介, 中戸研吾, 後藤淳, 重松真介, 金田楓, 羽手村昌宏. 冠動脈CTにおけるSuper-Resolution Deep Learning Reconstruction:模擬血管ファントムでの初期検討. 日本放射線技術学会雑誌. 2022. 78. 9. 1110-1110
榎本隆文, 永山泰教, 坂部大介, 中戸研吾, 後藤淳, 重松真介, 金田楓, 羽手村昌宏. 冠動脈CTにおけるSuper-Resolution Deep Learning Reconstruction:模擬血管ファントムでの初期検討. 日本放射線技術学会雑誌. 2022. 78. 9. 1110-1110

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Books (1)：

Dual-energy CT : 原理を理解し臨床で活用する
メジカルビュー社 2019 ISBN:9784758316125

Lectures and oral presentations (36)：

腹部画像診断に役立つスペクトラルCTの臨床活用術
(第82回日本医学放射線学会総会ランチョンセミナー 2023)
Usefulness of Super-resolution Deep-Learning-based Reconstruction for Coronary CT Angiography: A Clinical and Phantom Study
(ECR2023 2023)
Diagnosis of Lipid-poor Adrenal Adenomas: Performance Comparison between Non-contrast Spectral CT versus Chemical-Shift MRI
(RSNA 2022 2022)
Seeing More with Super-Resolution Deep-Learning CT Reconstruction: Physical Property and Clinical Potential
(RSNA 2022 2022)
Task-based Image Quality Assessments of Super-Resolution Deep-Learning Reconstruction for Coronary CT Angiography
(RSNA 2022 2022)

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Education (1)：

Kumamoto University

Professional career (1)：

医学博士 (熊本大学)

Awards (7)：

2023/09 - Japanese Society for the Advancement of Women's Imaging 優秀演題賞
2022/05 - 日本医学放射線学会総会 Cypos賞 Can dynamic hepatic CT be used to distinguish lipid-poor adrenal adenomas from adrenal metastases in patients with hepatocellular carcinoma?
2021/07 - 熊本大学放射線医学教室同門会髙橋国際賞
2021/05 - 「臨床画像」優秀論文賞イメージング・バイオマーカーとしての心臓周囲脂肪
2020/12 - Radiological Society of North America Identified for RadioGraphics Deep Learning-Based Reconstruction to Facilitate Lower Dose Pediatric CT: Technical Principles, Image Characteristics, and Clinical Implementations

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