A New MLEM Reconstruction Algorithm for Ultra-low Dose PET

被引:0
|
作者
Cierniak, Robert [1 ]
机构
[1] Czestochowa Tech Univ, Dept Intelligent Comp Syst, Czestochowa, Poland
来源
ADVANCES IN COMPUTATIONAL COLLECTIVE INTELLIGENCE, ICCCI 2024, PT II | 2024年 / 2166卷
关键词
ultra-low dose PET; model-based iterative reconstruction; image reconstruction from projections;
D O I
10.1007/978-3-031-70259-4_31
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This study introduces a novel ML-EM estimation method for reconstructing images in positron emission tomography. The concept proposed here utilizes a continuous-to-continuous data model, with the reconstruction problem expressed as a shift-invariant system. The primary objective of this research is to illustrate the methodology founded on probabilistic principles, emphasizing the consideration of statistical characteristics of PET signal data. The central focus of this paper is to establish that our method is grounded in statistical theory, offering alternative strategies to improve image resolution in low-dose PET scans.
引用
收藏
页码:406 / 418
页数:13
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