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

人工智能、信号和数据处理通过提高 PET 成像的灵敏度和检测效率来提高最终用户的灵活性

• 批准号: RGPIN-2016-05036
• 负责人: Michaud, JeanBaptiste
• 金额: $ 2.26万
• 依托单位: Université de Sherbrooke
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=659747
• 关键词: Artificial; intelligence; signal; data; processing

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.

该提案是一个新愿景的一部分，其中数字信号和数据处理，人工智能和分布式模块化分析可以大大提高正电子发射断层扫描（PET）的内在性能和最终用户的灵活性，这是一个共生和相互依赖的愿景，通常是技术进步，对系统级问题的理解和社会经济效率的限制。在短期内，该研究计划将减轻作为其他分辨率，TOF和探测器突破的副作用而出现的灵活性范式的压力。从中长期来看，这一愿景将通过对现有技术的创新补充，使所有PET最终用户受益，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发展。 * 取决于扫描仪的性能，如分辨率、对比度和灵敏度，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，所有这些对于该模式在全球医疗保健中的持续可用性至关重要。一些新的协议将需要高灵敏度，另一些则需要良好的对比度和分辨率，或者两者兼而有之：PET的成本效益发展需要灵活性，而全数字架构和上述愿景本身就提供了灵活性。 * 该计划侧重于灵敏度和检测效率，因为在考虑上述最终用户权衡时，这些是目前研究最少和影响最广的因素，通过这些因素可以快速获得最终用户的灵活性。PET技术的各种交织方面将立即受益于所提出的愿景：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，以提高效率，最大限度地减少其对图像质量的影响; 3a）算法最大化新SPAD探测器的动态范围，以提高灵敏度; 3b）在模块化嵌入式电源中实现新算法，作为固定到检测器本身而不是中央计算机的3D ASIC;以及4）设计先进的立体DOI技术，以减少定位不确定性并获得对比度和效率。 总的来说，这一愿景将导致新的科学（如果不是商业）努力，允许迄今为止在PET中闻所未闻的数字技术和人工智能的适应，以规避许多已知的问题和限制，并为该模式开辟新的可能性。