ISSN 1004-4140
CN 11-3017/P
LI X M, XIE Q G, WAN L. All-Digital PET Imaging Software Based on Plug and Imaging[J]. CT Theory and Applications, 2024, 33(4): 433-447. DOI: 10.15953/j.ctta.2024.013. (in Chinese).
Citation: LI X M, XIE Q G, WAN L. All-Digital PET Imaging Software Based on Plug and Imaging[J]. CT Theory and Applications, 2024, 33(4): 433-447. DOI: 10.15953/j.ctta.2024.013. (in Chinese).

All-Digital PET Imaging Software Based on Plug and Imaging

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  • Received Date: November 13, 2023
  • Revised Date: March 13, 2024
  • Accepted Date: March 28, 2024
  • Available Online: April 14, 2024
  • Traditional positron emission tomography (PET) systems apply analog circuits for signal processing and achieve coincidence event detection through coincident circuitry. However, these systems suffer from a significant loss of information during projection and image data processing, leading to poor algorithm scalability. In contrast, All-Digital PET systems leverage precise sampling and comprehensive digital processing to simplify hardware design while maximizing software capabilities. These advanced systems rely on software algorithms to handle more operations, thereby providing complete process data, abundant algorithms, and convenient optimization for replacement. By treating detectors and algorithms as fundamental “building blocks,” the plug and imaging (PnI) platform constructs imaging protocols, algorithms, and equipment layers to define the imaging process, extend algorithmic capabilities, and support the construction of diverse animal or clinical PET system types. Moreover, integrating PnI into All-Digital PET systems allows for early information mining from scintillation pulse data levels rather than at the image level, facilitating flexible additional algorithm integration. Based on the aforementioned background, in this study, we critically investigated PnI software-related research advancements, precisely elucidating the comprehensive structure of All-Digital PET systems, architectural flowcharting of the imaging process, and exemplary application cases. Our primary objective was to enhance flexibility for scientists involved in constructing All-Digital PET research instruments while providing valuable references for the expeditious and efficient development of diverse PET systems alongside software algorithmic enhancements.

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