PET系统的脑成像透视

IF 1.2 Q3 Computer Science Bio-Algorithms and Med-Systems Pub Date : 2021-12-01 DOI:10.1515/bams-2021-0178
S. Majewski
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引用次数: 4

摘要

摘要在对专用大脑PET扫描仪(PET技术的关键实现)的未来进行部分回顾和部分尝试时,我们假设我们仍在发展道路上,为了开发最佳的大脑成像仪,还有很多工作要做。针对特定的成像任务和协议进行了优化,也可移动,除了灵敏度和分辨率的预期改进外,还可在PET中心外使用。为了使这种多应用概念更加实用,优选灵活、适应性强的设计。TOF性能的提高极大地促进了这项任务,该性能允许在不产生图像伪影的情况下实现更开放、可调节、有限的角度覆盖几何形状。由于技术限制和高成本,在全身实现均匀的非常高的分辨率是不现实的,因此使用中等分辨率全身扫描仪(如J-PET)与非常高性能的大脑成像器相结合的混合系统可能是一种非常有吸引力的方法。此外,还可以在全身或长轴长度成像器中使用放大插件,以更高的分辨率对选定目标进行可视化。此外,应开发将PET与康普顿成像相结合的多伽马成像仪,以实现多示踪剂成像。
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Perspectives of brain imaging with PET systems
Abstract In this partial review and partial attempt at vision of what may be the future of dedicated brain PET scanners, the key implementations of the PET technique, we postulate that we are still on a development path and there is still a lot to be done in order to develop optimal brain imagers. Optimized for particular imaging tasks and protocols, and also mobile, that can be used outside the PET center, in addition to the expected improvements in sensitivity and resolution. For this multi-application concept to be more practical, flexible, adaptable designs are preferred. This task is greatly facilitated by the improved TOF performance that allows for more open, adjustable, limited angular coverage geometries without creating image artifacts. As achieving uniform very high resolution in the whole body is not practical due to technological limits and high costs, hybrid systems using a moderate-resolution total body scanner (such as J-PET) combined with a very high performing brain imager could be a very attractive approach. As well, as using magnification inserts in the total body or long-axial length imagers to visualize selected targets with higher resolution. In addition, multigamma imagers combining PET with Compton imaging should be developed to enable multitracer imaging.
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来源期刊
Bio-Algorithms and Med-Systems
Bio-Algorithms and Med-Systems MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
3.80
自引率
0.00%
发文量
3
期刊介绍: The journal Bio-Algorithms and Med-Systems (BAMS), edited by the Jagiellonian University Medical College, provides a forum for the exchange of information in the interdisciplinary fields of computational methods applied in medicine, presenting new algorithms and databases that allows the progress in collaborations between medicine, informatics, physics, and biochemistry. Projects linking specialists representing these disciplines are welcome to be published in this Journal. Articles in BAMS are published in English. Topics Bioinformatics Systems biology Telemedicine E-Learning in Medicine Patient''s electronic record Image processing Medical databases.
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