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Tomographic Image Reconstruction Based on Minimization of Symmetrized Kullback-Leibler Divergence
https://tokushima-u.repo.nii.ac.jp/records/2007341
https://tokushima-u.repo.nii.ac.jp/records/200734122a9da93-3d65-451e-bfae-fe1765f40270
| 名前 / ファイル | ライセンス | アクション |
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MathProEng_2018_8973131.pdf (2.1 MB)
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| Item type | 文献 / Documents(1) | |||||||||||||||||||||||
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| 公開日 | 2020-03-26 | |||||||||||||||||||||||
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| アクセス権 | open access | |||||||||||||||||||||||
| 資源タイプ | ||||||||||||||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||||||||||||||
| 資源タイプ | journal article | |||||||||||||||||||||||
| 出版社版DOI | ||||||||||||||||||||||||
| 関連識別子 | https://doi.org/10.1155/2018/8973131 | |||||||||||||||||||||||
| 関連名称 | 10.1155/2018/8973131 | |||||||||||||||||||||||
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| 出版タイプ | VoR | |||||||||||||||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||||||||||||||
| タイトル | ||||||||||||||||||||||||
| タイトル | Tomographic Image Reconstruction Based on Minimization of Symmetrized Kullback-Leibler Divergence | |||||||||||||||||||||||
| 著者 |
笠井, 亮佑
× 笠井, 亮佑
WEKO
928
× 山口, 雄作
× 兒島, 雄志× 吉永, 哲哉
WEKO
1587
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| 抄録 | ||||||||||||||||||||||||
| 内容記述 | Iterative reconstruction (IR) algorithms based on the principle of optimization are known for producing better reconstructed images in computed tomography. In this paper, we present an IR algorithm based on minimizing a symmetrized Kullback-Leibler divergence (SKLD) that is called Jeffreys’ J-divergence. The SKLD with iterative steps is guaranteed to decrease in convergence monotonically using a continuous dynamical method for consistent inverse problems. Specifically, we construct an autonomous differential equation for which the proposed iterative formula gives a first-order numerical discretization and demonstrate the stability of a desired solution using Lyapunov’s theorem. We describe a hybrid Euler method combined with additive and multiplicative calculus for constructing an effective and robust discretization method, thereby enabling us to obtain an approximate solution to the differential equation.We performed experiments and found that the IR algorithm derived from the hybrid discretization achieved high performance. | |||||||||||||||||||||||
| 書誌情報 |
en : Mathematical Problems in Engineering 巻 2018, p. 8973131, 発行日 2018-07-17 |
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| 収録物識別子 | 15635147 | |||||||||||||||||||||||
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| 収録物識別子タイプ | NCID | |||||||||||||||||||||||
| 収録物識別子 | AA11947206 | |||||||||||||||||||||||
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| 出版者 | Hindawi | |||||||||||||||||||||||
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| 権利情報 | Copyright © 2018 Ryosuke Kasai et al.This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. | |||||||||||||||||||||||
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| 識別子 | 340048 | |||||||||||||||||||||||
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| 言語 | eng | |||||||||||||||||||||||
