CPS: Medium: Collaborative Research: Human-on-the-Loop Control for Smart Ultrasound Imaging

CPS：中：协作研究：智能超声成像的人在环控制

• 批准号: 1837499
• 负责人: Michael Zavlanos
• 金额: $ 60万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1837499&HistoricalAwards=false
• 关键词: CPS; Medium; Collaborative; Research; Human

Due to low operating cost and patient safety, ultrasound is widely accepted as one of the best forms of medical imaging compared to similar technologies, such as Computer Tomography (CT) scans or Magnetic Resonance Imaging (MRI). Still, there can be large variability in image quality obtained by different experts imaging the same patient, which can affect successful diagnosis and patient treatment. This problem becomes even more pronounced across patients. Consequently, to decrease this variability this project will develop imaging techniques that are not passive but are based on real-time ultrasound beam control and adaptation, while facilitating best use of operator expertise to obtain the most informative images. Such new active ultrasound systems, where expert users with varying levels of training interact with a smart ultrasound device to improve medical imaging and facilitate diagnosis, will provide significant performance gains compared to present systems that are only manually controlled. This project will also have a significant societal impact in accurate, safe, and cost-effective diagnosis of many medical conditions, such as cancers or liver fibrosis. For instance, the use of such systems for breast cancer diagnosis will significantly reduce the number of unnecessary biopsies, which currently cost more than $1 billion annually in the US alone. At the same time this technology can enable a variety of other imaging applications that rely on different forms of ultrasound, such as mapping of the heart chambers using Doppler ultrasound or identifying the mechanical properties of materials in structures for failure prognosis.Specifically, the goal of this project is the development of an active ultrasound system where user expertise is employed to refine the control process, while autonomous elasticity (or viscoelasticity) mapping improves image quality and allows human operator to best use their skills for both optimization and diagnosis. The project's research products include: (i) data fusion techniques for ultrasound elastography; (ii) methods for interactive ultrasound elastography; and (iii) framework for safe and efficient device implementation. The ultrasound system will be validated on a test-bed based on suitable laboratory phantoms and real-time control of existing ultrasound devices. Investigators will focus on the unique aspects of this novel paradigm that, compared to existing methods, include: (1) new active, user-machine, imaging techniques improving on the characterization of the mechanical properties of tissue; and (2) the systematic transition of algorithms and user interfaces to embedded computers for safe execution by the device. This requires overcoming intellectual challenges related to the integration of visco-elastography mapping and human-on-the-loop ultrasound control, as well as synthesis of new theoretical results drawing from computational mechanics, controls and estimation, and embedded systems design. The project also has extensive education and outreach components, including curriculum development focused on design of safety-critical medical cyber-physical systems that exhibit highly dynamical system behaviors and plant uncertainty, human interactions, and the need for real-time implementation. The outreach component of this project will also improve the pre-college students' awareness of the potential and attractiveness of a research and engineering career.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

由于操作成本低和患者安全，与类似技术（如计算机断层扫描（CT）扫描或磁共振成像（MRI））相比，超声被广泛接受为最佳医学成像形式之一。尽管如此，由不同专家对同一患者进行成像所获得的图像质量可能存在很大的差异，这可能影响成功的诊断和患者治疗。这个问题在患者中变得更加突出。因此，为了减少这种变化，该项目将开发成像技术，不是被动的，而是基于实时超声波束控制和适应，同时促进最好地利用操作员的专业知识，以获得最丰富的图像。这种新的主动超声系统，其中具有不同训练水平的专家用户与智能超声设备交互以改善医学成像并促进诊断，与仅手动控制的现有系统相比，将提供显著的性能增益。该项目还将对许多医疗条件（如癌症或肝纤维化）的准确，安全和具有成本效益的诊断产生重大的社会影响。例如，使用这种系统进行乳腺癌诊断将大大减少不必要的活检数量，目前仅在美国每年就花费超过10亿美元。同时，这项技术还可以实现其他各种依赖于不同形式的超声的成像应用，例如使用多普勒超声绘制心腔图或识别结构中材料的机械性能以进行故障预测。具体而言，该项目的目标是开发一种主动超声系统，其中使用用户专业知识来完善控制过程，而自主弹性（或粘弹性）映射改善了图像质量，并允许操作人员最好地使用他们的技能来进行优化和诊断。该项目的研究成果包括：（一）超声弹性成像的数据融合技术;（二）交互式超声弹性成像方法;以及（三）安全有效的设备实施框架。超声系统将在基于适当实验室体模和现有超声设备实时控制的试验台上进行确认。与现有方法相比，研究者将重点关注这种新型范例的独特方面，包括：（1）新的主动、用户-机器成像技术，改善了组织机械特性的表征;（2）算法和用户界面系统性地过渡到嵌入式计算机，以便器械安全执行。这需要克服与粘弹性成像映射和人在环超声控制的集成相关的智力挑战，以及从计算力学，控制和估计以及嵌入式系统设计中提取的新理论结果的合成。该项目还具有广泛的教育和推广组成部分，包括课程开发，重点是安全关键医疗网络物理系统的设计，这些系统表现出高度动态的系统行为和工厂不确定性，人类互动以及实时实施的必要性。该项目的推广部分也将提高大学预科学生对研究和工程职业的潜力和吸引力的认识。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

VarNet: Variational Neural Networks for the Solution of Partial Differential Equations

• 发表时间: 2019-12
• 期刊: ArXiv
• 作者: Reza Khodayi-mehr;M. Zavlanos

Plane wave elastography: a frequency-domain ultrasound shear wave elastography approach

平面波弹性成像：频域超声剪切波弹性成像方法

• DOI: 10.1088/1361-6560/ac01b8
• 发表时间: 2021
• 期刊: Physics in Medicine & Biology
• 影响因子: 3.5
• 作者: Khodayi-mehr, Reza;Urban, Matthew W;Zavlanos, Michael M;Aquino, Wilkins
• 通讯作者: Aquino, Wilkins

A Reinforcement Learning-Informed Pattern Mining Framework for Multivariate Time Series Classification

用于多元时间序列分类的强化学习模式挖掘框架

• 发表时间: 2022
• 期刊: 31st International Joint Conference on Artificial Intelligence (IJCAI
• 作者: Gao, Ge;Gao, Qitong;Yang, Xi;Pajic, Miroslav;Chi, Min
• 通讯作者: Chi, Min

Offline Policy Evaluation for Learning-based Deep Brain Stimulation Controllers

• DOI: 10.1109/iccps54341.2022.00014
• 发表时间: 2022-05
• 期刊: 2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)
• 作者: Qitong Gao;Stephen L. Schmidt;Karthik Kamaravelu;D. Turner;W. Grill;Miroslav Pajic