SCH: CAREER: Co-Robotic Ultrasound Sensing in Bioengineering

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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.