2023年度研究報告

原著および査読付国際会議論文

  1. Keisuke Usui, Sae Kamiyama, Akihiro Arita, Koichi Ogawa, Hajime Sakamoto, Yasuaki Sakano，Shinsuke Kyogoku，Hiroyuki Daida,　“Reducing image artifacts in sparse projection CT using conditional generative adversarial networks,” Journal of Medical and Biological Engineering, DOI: https://doi.org/10.21203/rs.3.rs-3304857/v1, 2023

  2. Momoka Yamada, Kazumi Murata, and Koichi Ogawa, “Deconvolution-based Image Recovery for Dynamic Study With Multi-pinhole SPECT System,” IEEE Nuclear Science Symposium and Medical Imaging Conference,DOI: , 2023

  3. Soya Yagi, Keisuke Usui, and Koichi Ogawa,” Scatter and Beam Hardening Correction of Cone Beam CT with a Convolutional Neural Network,” IEEE Nuclear Science Symposium and Medical Imaging Conference, DOI: , 2023

  4. Akihiro Arita, Keisuke Usui, Syuhei Shibukawa, Masami Goto, Yasuaki Sakano, Shinsuke Kyogoku, Isao Muro, Hiroyuki Daida and Koichi Ogawa, ”Reduction of Motion Artifacts in Head Magnetic Resonance Imaging using Conditional Generative Adversarial Networks,” IEEE Nuclear Science Symposium and Medical Imaging Conference, DOI: , 2023

  5. 島田良,村田一心,尾川浩一, “深層学習を用いたマルチピンホールSPECTシステムの空間分解能の改善,” Med Imag Tech. Vol. 41，No.3, pp.124-128、2024

著書

解説論文、査読のない論文

  1. 尾川浩一,” フォトンカウンティングCTが拓く革新的医療“、MDB Technology Forecast Report、日本能率協会、2024

国際会議における発表

  1. Momoka Yamada, Kazumi Murata, and Koichi Ogawa, “Deconvolution-based Image Recovery for Dynamic Study With Multi-pinhole SPECT System,” IEEE Nuclear Science Symposium and Medical Imaging Conference, Vancouver (Canada), Nov. 4-11, 2023

  2. Soya Yagi, Keisuke Usui, and Koichi Ogawa,” Scatter and Beam Hardening Correction of Cone Beam CT with a Convolutional Neural Network,” IEEE Nuclear Science Symposium and Medical Imaging Conference, Vancouver (Canada), Nov. 4-11, 2023

  3. Akihiro Arita, Keisuke Usui, Syuhei Shibukawa, Masami Goto, Yasuaki Sakano, Shinsuke Kyogoku, Isao Muro, Hiroyuki Daida and Koichi Ogawa, ”Reduction of Motion Artifacts in Head Magnetic Resonance Imaging using Conditional Generative Adversarial Networks,” IEEE Nuclear Science Symposium and Medical Imaging Conference, Vancouver (Canada), Nov. 4-11, 2023

  4. Keisuke Usui and Koichi Ogawa,, “Simulated Cone-Beam Computed Tomography-Based Pseudo-Computed Tomography Images Using Conditional Generative Adversarial Network”, AAPM 2024, July 21-25Los Angels USA

国内の学会での発表

  1. 丹羽 英之, 尾川 浩一,” 3次元類似性駆動型メディアン正則化を用いたピンホールSPECTの画像再構成”, 第42回日本医用画像工学会大会予稿集, pp.183-184, 2023 (大阪市)

  2. 福士　晴哉, 国枝　悦夫, 尾川 浩一,” 深層学習を用いた放射線肺臓炎の領域抽出とその放射線治療計画への応用”, 第42回日本医用画像工学会大会予稿集, pp.132-133, 2023 (大阪市) 　

  3. 臼井桂介、尾川浩一, “条件付き敵対的生成ネットワークを用いたスパース投影 CT の画像アーチファクトの低減,” 第5回日本メディカルAI学会学術集会、 G-50、2023/6/17-18　

  4. Soya Yagi, Keisuke Usui, Koichi Ogawa, “Correction of Scatter and Beam Hardening Effect in Cone Beam CT Using Deep Learning,” 第126回日本医学物理学会学術大会報文集（医学物理、vol.43、sup.3）, p.90, 2023/9/15-17(広島市) 　

  5. Ryoga Okachi, Koichi Ogawa, “A study on pinhole geometry and number of pinholes in a three-detector multi-pinhole SPECT system,” 第126回日本医学物理学会学術大会報文集（医学物理、vol.43、sup.3）, p.116, 2023/9/15-17(広島市) 　

  6. Momoka Yamada, Kazumi Murata, Koichi Ogawa、“Improvement of Spatial Resolution in Pinhole SPECT System Using Deconvolution Method,” 第126回日本医学物理学会学術大会報文集（医学物理、vol.43、sup.3）, p.117, 2023/9/15-17(広島市)

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