SCH: CAREER: Co-Robotic Ultrasound Sensing in Bioengineering

超声成像虽然经常用于医疗保健，但仍面临三个重要问题的挑战。首先，由于执行成像任务所需的努力，非常显著比例的超声医师（63 - 91%）发展为肌肉骨骼疾病。其次，超声成像受到深度增加时分辨率损失的限制（例如，在肥胖患者的成像中），显著限制了常规超声成像的成像价值。最后，超声成像本质上最常见的是定性的，而定量成像（例如，超声波信号速度的测量）受到限制。对于各种器官和疾病的更准确成像存在显著差距和需求。所有这些问题都阻碍了超声技术为医院内更广泛的患者提供服务的潜在好处，最重要的是医院外，包括护理点和家庭。所有这些看似不同的问题都可以通过协作机器人和多波超声框架来解决和解决。该提案的目的是表征机器人、超声物理学、信号处理、机器学习和生物工程交叉点的基本原理，这将使新一代先进的超声成像技术能够为医院、护理点和家庭中更广泛的人群提供具有成本效益的精确介入引导和高质量的定量诊断成像。此外，该提案强调了以下教育目标：（1）依靠MUSiiC工具包创建动手机器人成像本科生/研究生培训课程;（2）将研究成果带到当地学校，包括百年高中，并让学生参与研究;（3）在高中和大学教室部署低成本无线超声系统和重量轻且对人类安全的机器人。该提案的研究目标是表征机器人，超声物理学，信号处理，机器学习和生物工程交叉点的基本原理，这将使新一代先进的超声成像技术能够为医院，护理点和家庭的更广泛人群提供具有成本效益的精确介入指导和高质量的定量诊断成像。为实现这一目标，该提案包括一个综合研究教育计划，其中包括三个相互补充和相互关联的研究重点。推力1：新型多波超声和机器人成像设备专注于新型多波超声成像架构和基于物理的模拟，这些模拟描述了它们在可变校准和机器人跟踪精度以及超声传感器的波束宽度和几何限制下的性能。 具体而言，该项目提出了超声智能工具，协作机器人多波超声系统以及主动校准平台和验证。推力二：Robust Sensing and Co-Robotic Imaging专注于使用Thrust 1的模型、架构和设备，为手术和介入引导提供强大的传感，并设计和实现具有强大传感和协作机器人智能的新成像算法。具体来说，该项目使用了一种新型的热成像算法，利用了Thrust 1中描述的独特的多波超声架构。此外，我们探索合作机器人成像，以大大提高超声分辨率，利用合成孔径重建引导的机器人的精确和准确的运动轨迹。 推力3：教育的重点是将研究成果纳入高中，本科和研究生教育，同时强调在生物医学科学和工程中代表性不足的个人（非洲裔美国人和妇女）的参与。该提案还将把研究成果带到包括百年高中在内的当地学校，并让他们的学生参与研究。这可以很容易地实现这一点，依靠该团队的医疗超声成像和干预合作实验室（MUSiiC）软件工具包，并使智能手机和平板电脑控制超声系统。该计划还包括部署一些低成本的无线超声系统，沿着重量轻、对人类安全的机器人，用于高中和大学的教室。这三项研究的结果将应用于三个临床试验台的系统，包括癌症干预、导管插入术和诊断成像。

Ultrasound imaging, while frequently used in heathcare, remains challenged by three important issues. First, a very significant percentage of ultrasonographers (63-91%) develop musculoskeletal disorders due to effort required to perform imaging tasks. Second, ultrasound imaging is limited by loss of resolution at increasing depths (e.g., in imaging of obese patients), significantly limiting imaging value with conventional ultrasound imaging. Finally, ultrasound imaging is most commonly qualitative in nature, and quantitative imaging (e.g., measurement of the speed of the ultrasounds signal) has been limited. There is significant gap and need for more accurate imaging of various organs and diseases. All these issues hinder unleashing the potential benefit of ultrasound technology serving a wider sector of patients in hospitals and most importantly outside hospitals, including point-of-cares and homes. All these seemingly distinct issues can be tackled and addressed via a co-robotic and multi-wave ultrasound framework. The objective of this proposal is to characterize fundamental principles at the intersection of robotics, ultrasound physics, signal processing, machine learning and bioengineering, which will enable a new generation of advanced ultrasound imaging technologies capable of providing cost-effective precise interventional guidance and high-quality quantitative diagnostic imaging to a wider sector of people at hospitals, points-of-care, and homes. Additionally, this proposal emphasizes the following educational objectives: (1) create hands-on robotic imaging undergraduate/graduate training curriculum relying on the MUSiiC toolkit; (2) bring research results to local schools including Centennial High School and involve their students in research; and (3) deploy low-cost wireless ultrasound systems and light-weight and human-safe robots in high schools and university classrooms. The research objective of this proposal is to characterize fundamental principles at the intersection of robotics, ultrasound physics, signal processing, machine learning and bioengineering, which will enable a new generation of advanced ultrasound imaging technologies capable of providing cost-effective precise interventional guidance and high-quality quantitative diagnostic imaging to a wider sector of people at hospitals, points-of-care, and homes. To achieve this objective, this proposal includes an integrated research-education plan consisting of three complementary and interconnected research thrusts. Thrust 1: Novel Multi-wave Ultrasonic and Robotic Imaging Devices focuses on novel multi-wave ultrasound imaging architectures and physics-based simulations that describe their performance under variable calibration and robot tracking accuracies, and beam-width and geometry limitations of ultrasound sensors. Specifically, the project proposes ultrasonically smart tools, co-robotic multi-wave ultrasound systems, and active calibration platform and validation. Thrust 2: Robust Sensing and Co-Robotic Imaging focuses on using models, architectures and devices from Thrust 1 to endow surgical and interventional guidance with robust sensing and to devise and enable new imaging algorithms with both robust sensing and co-robotic intelligence. Specifically, the project uses a novel thermal imaging algorithm leveraging the unique multi-wave ultrasound architecture described in Thrust 1. Additionally, we explore co-robotic imaging to substantially enhance ultrasound resolution utilizing synthetic aperture reconstruction guided by the robot's precise and accurate motion trajectory. Thrust 3: Education focuses on integrating research results into education at the high school, undergraduate, and graduate levels, while emphasizing participation by an underrepresented individuals (African American and women) in Biomedical Sciences and Engineering. The proposal will also bring research results to local schools including Centennial High School and involve their students in research. This can easily achieve this by relying on the team's Medical UltraSound Imaging and Intervention Collaboratory (MUSiiC) software toolkit and enabling smart phone and tablets to control ultrasound systems. The plan also includes deployment of a number of low-cost wireless ultrasound systems, along with light-weight and human-safe robots, to high school and university classrooms. The results from all three thrusts will be applied to systems for three clinical testbed setups, including cancer intervention, catheterization, and diagnostic imaging.