Towards New Frontiers in Computer Assisted Image Guidance with Next Generation Point of Care Ultrasound

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In recent years, image-guided solutions using real-time ultrasound imaging have revolutionized computer assisted intervention systems. However, current systems are limited to specialized centres equipped with expensive specialized motion tracking equipment and advanced, expensive imaging devices. A solution to large-scale distribution of these systems is point-of-care ultrasound, which enables image acquisition on mobile devices at much lower cost. However, potential point-of-care operators are novices/untrained in ultrasound. Operators struggle with the hand-eye coordination needed to obtain the correct ultrasound imaging data, intuitively interpret the data, and to use ultrasound as an effective guide. What is needed is a significant leap in technologies that will improve the ease-of-use of ultrasound for specific image-guided applications. This research program will develop fundamental technologies to lead the transformation of next generation computer-assisted intervention systems, enabled with point-of-care ultrasound devices. Better data acquisition will be achieved by developing new methodologies that accurately determine the underlying tissue properties using adaptive beamforming. Accurate estimation of tissue properties will be used to enhance the reconstruction of 3D ultrasound volumes without the need for specialized tracking devices that are bulky and hinder workflow. Better interpretation will be addressed by using machine learning solutions that automatically identify key anatomical landmarks in 3D ultrasound, segment relevant anatomical boundaries, and fuse 3D ultrasound with pre-operative images to take advantage of complimentary anatomical information. Validation will be established in an iterative design process. An example design application is spinal anesthesia, for guiding epidural needle injection procedures. All these techniques will be implemented individually or together on commercial point-of-care ultrasound machines starting with the Canadian-made Clarius. These techniques will make several image-guided procedures, including spinal anesthesia, easier and more accurate than current state-of-the-art in these procedures. Hence, this research program will enable widespread deployment of image-guided technology. The proposed program will train three PhD and three MSc students, as well as five undergraduate students. A detailed training plan that allows individuals to reach their full potential is integrated within the development of research objectives to ensure a high quality, interactive, flourishing, and an equitable research environment for HQP as per UBC Equity and Diversity Strategic Plan and Policy #2.