直近一年間の累計
アクセス数 : ?
ダウンロード数 : ?
ID 119336
タイトル別表記
人体ファントムライブラリに基づく仮想コーンビームCTの開発と元素分布分析への応用
著者
下村, 泰生 徳島大学大学院保健科学研究科(保健学専攻)
Fujiwara, Daiyu Tokushima University
Inoue, Yuki Tokushima University
Takeya, Atsushi Tokushima University
Ohta, Takeshi The University of Tokyo
Nozawa, Yuki The University of Tokyo
Imae, Toshikazu The University of Tokyo
Nawa, Kanabu The University of Tokyo
Nakagawa, Keiichi The University of Tokyo
キーワード
Monte Carlo simulation
Cone-beam computed tomography
Human phantom
Material decomposition
Artificial intelligence
Computer vision
コーンビームCT
人体ファントム
元素分析
人工知能
コンピュータービジョン
資料タイプ
学位論文
抄録
Purpose: The purpose of this study is to develop a virtual CBCT simulator with a head and neck (HN) human phantom library and to demonstrate the feasibility of elemental material decomposition (EMD) for quantitative CBCT imaging using this virtual simulator.
Methods: The library of 36 HN human phantoms were developed by extending the ICRP 110 adult phantoms based on human age, height, and weight statistics. To create the CBCT database for the library, a virtual CBCT simulator that simulated the direct and scattered X-ray on a flat panel detector using ray-tracing and deep-learning (DL) models was used. Gaussian distributed noise was also included on the flat panel detector, which was evaluated using a real CBCT system. The usefulness of the virtual CBCT system was demonstrated through the application of the developed DL-based EMD model for case involving virtual phantom and real patient.
Results: The virtual simulator could generate various virtual CBCT images based on the human phantom library, and the prediction of the EMD could be successfully performed by preparing the CBCT database from the proposed virtual system, even for a real patient. The CBCT image degradation owing to the scattered X-ray and the statistical noise affected the prediction accuracy, although these effects were minimal. Furthermore, the elemental distribution using the real CBCT image was also predictable.
Conclusions: This study demonstrated the potential of using computer vision for medical data preparation and analysis, which could have important implications for improving patient outcomes, especially in adaptive radiation therapy.
掲載誌名
Physica Medica
ISSN
1724191X
11201797
cat書誌ID
AA12796015
出版者
Elsevier
113
開始ページ
102648
発行日
2023-09-04
備考
内容要旨・審査要旨・論文本文の公開
本論文は,著者Taisei Shimomuraの学位論文として提出され,学位審査・授与の対象となっている。
EDB ID
出版社版DOI
出版社版URL
フルテキストファイル
言語
eng
著者版フラグ
博士論文全文を含む
文科省報告番号
甲第3804号
学位記番号
甲保第67号
学位授与年月日
2024-03-22
学位名
博士(保健学)
学位授与機関
徳島大学
部局
医学系