Artificial intelligence, signal and data processing towards greater end-user flexibility through increased sensitivity and detection efficiency in PET imaging

这项提议是一个新愿景的一部分，在这个愿景中，数字信号和数据处理、人工智能和分布式模块分析可以极大地改善正电子发射断层扫描(PET)的内在性能和最终用户的灵活性，这一愿景是共生的，相互依赖于通常的技术进步、对系统层面问题的理解和社会经济效率的限制。在短期内，该研究计划将缓解作为其他分辨率、TOF和探测器突破的副作用而出现的灵活性范例的压力。在中长期内，这一愿景将通过对现有技术的创新补充，使所有PET终端用户独特地受益，通过新的放射性示踪剂或新的常规护理和研究方案的出现，帮助这种分子和基因组成像模式在未来几十年继续增长。根据分辨率、对比度和灵敏度等扫描仪性能的不同，最终用户面临着图像质量、注射剂量和扫描长度之间的重大权衡，直接影响任何给定成像协议的灵活性、科学回报和成本/效益比，所有这些都是该设备在全球医疗保健中持续可用的首要重要性。一些新的协议将需要高灵敏度，另一些需要良好的对比度和分辨率，或者两者兼而有之：PET的经济高效的发展需要灵活性，这是全数字架构和前述视觉固有的。该计划重点关注灵敏度和检测效率，因为在考虑上述最终用户之间的权衡时，这些是目前研究最少、影响最广的因素，通过这些因素可以快速获得最终用户的灵活性。PET技术的各个相互交织的方面将立即受益于拟议的愿景：1)优化我最近展示的一种新型人工智能方法，将检测效率提高50%至200%；2)改进图像重建方法，以考虑到提高的效率，将其对图像质量的影响降至最低；3a)通过算法最大化新型SPAD探测器的动态范围，以提高灵敏度；3b)以模块化嵌入式电源的形式实施新算法，将其作为固定在探测器本身的3D ASIC而不是中央计算机；以及4)设计先进的立体DOI技术，以减少定位不确定性，获得对比度和效率。总体而言，这一愿景将带来新的科学努力，如果不是商业努力的话，允许采用数字技术和人工智能，以绕过许多已知的问题和限制，并为这种模式打开新的可能性。

This proposal is part of a novel vision where digital signal and data processing, artificial intelligence and distributed modular analysis can substantially improve both the intrinsic performance and end-user flexibility of Positron Emission Tomography (PET), a vision symbiotic and interdependent on the usual advances in technology, comprehension of system-level issues and socio-economic efficiency constraints. In the short term, the research program will mitigate the pressure on the flexibility paradigm emerging as side-effects of other resolution, TOF and detector breakthroughs. In the mid to long term, the vision will uniquely benefit all PET end-users through innovative complements to existing technology, helping this molecular and genomic imaging modality continue to grow in the next decades through the emergence of new radiotracers or new routine care and research protocols. Depending on scanner performance like resolution, contrast and sensitivity, the end-user faces a significant trade-off between image quality, injected dose and scan length, directly impacting the flexibility, scientific return and cost/benefit ratio of any given imaging protocol, all of primordial importance in the continued availability of the modality in healthcare worldwide. Some new protocols will require high sensitivity, others good contrast and resolution, or both: the cost effective evolution of PET requires flexibility, which an all-digital architecture and the aforementioned vision inherently provide. The program focuses on sensitivity and detection efficiency because, when considering the above end-user trade-off, these are currently the most under-studied and wide-reaching factors through which end-user flexibility can be gained quickly. Varied interwoven aspects of PET technology will immediately benefit from the proposed vision: 1) optimization of a novel artificial intelligence method I recently demonstrated to improve detection efficiency by 50 to 200%; 2) refinement of image reconstruction methods to account for the improved efficiency, minimizing its impact on image quality; 3a) algorithmic maximization of new SPAD detectors' dynamic range to improve sensitivity; 3b) implementation of the new algorithms in modular embedded power as a 3D ASIC affixed to the detector itself instead of a central computer; and 4) design of an advanced stereoscopic DOI technique to decrease localization uncertainties and gain both contrast and efficiency. Overall this vision will lead to new scientific if not commercial endeavors, allowing adaptations of digital techniques and artificial intelligence mostly unheard of in PET until now to circumvent many known problems and limitations and to open new possibilities for the modality.