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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2022.6
- 수록면
- 2,204 - 2,212 (9page)
- DOI
- https://doi.org/10.1016/j.net.2021.12.021
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초록· 키워드
오류제보하기
Recently, the demand for alpha imaging detectors for quantifying the distributions of alpha particles hasincreased in various fields. This study aims to reconstruct a high-resolution image from an alpha imagingdetector by applying a super-spatial resolution method combined with the maximum-likelihoodexpectation maximization (MLEM) algorithm. To perform the super-spatial resolution method, severalimages are acquired while slightly moving the detector to predefined positions. Then, a forward modelfor imaging is established by the system matrix containing the mechanical shifts, subsampling, andmeasured point-spread function of the imaging system. Using the measured images and system matrix,the MLEM algorithm is implemented, which converges towards a high-resolution image. We evaluatedthe performance of the proposed method through the Monte Carlo simulations and phantom experiments. The results showed that the super-spatial resolution method was successfully applied to the alphaimaging detector. The spatial resolution of the resultant image was improved by approximately 12% usingfour images. Overall, the study's outcomes demonstrate the feasibility of the super-spatial resolutionmethod for the alpha imaging detector. Possible applications of the proposed method include highresolution imaging for alpha particles of in vitro sliced tissue and pre-clinical biologic assessments fortargeted alpha therapy
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