ID | 118919 |
著者 |
アボウ アルオラ, オマル
Tanta University
山口, 雄作
Shikoku Medical Center for Children and Adults
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キーワード | computed tomography
iterative reconstruction
ordered-subsets algorithm
maximum-likelihood expectation-maximization
multiplicative algebraic reconstruction technique
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資料タイプ |
学術雑誌論文
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抄録 | Iterative image reconstruction algorithms have considerable advantages over transform methods for computed tomography, but they each have their own drawbacks. In particular, the maximum-likelihood expectation-maximization (MLEM) algorithm reconstructs high-quality images even with noisy projection data, but it is slow. On the other hand, the simultaneous multiplicative algebraic reconstruction technique (SMART) converges faster at early iterations but is susceptible to noise. Here, we construct a novel algorithm that has the advantages of these different iterative schemes by combining ordered-subsets EM (OS-EM) and MART (OS-MART) with weighted geometric or hybrid means. It is theoretically shown that the objective function decreases with every iteration and the amount of decrease is greater than the mean between the decreases for OS-EM and OS-MART. We conducted image reconstruction experiments on simulated phantoms and deduced that our algorithm outperforms OS-EM and OS-MART alone. Our algorithm would be effective in practice since it incorporates OS-EM, which is currently the most popular technique of iterative image reconstruction from noisy measured projections.
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掲載誌名 |
Mathematics
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ISSN | 22277390
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出版者 | MDPI
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巻 | 10
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号 | 22
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開始ページ | 4277
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発行日 | 2022-11-15
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権利情報 | This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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言語 |
eng
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部局 |
医学系
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