Image-guided robot-assisted diagnostic ultrasound

Ultrasound technicians are often required to hold the transducers in awkward positions for prolonged periods of time, while exerting large forces. As a result, they suffer from an unusually high incidence of musculoskeletal disorders. A novel robot-assisted tele-operation system has been proposed at the University of British Columbia to alleviate these problems. This thesis is part of this larger tele-operation system for diagnostic ultrasound. It contributes several novel real-time feature tracking methods for ultrasound images, the development of the "ultrasound visual servoing" concept, the design and implementation of the image controller and the user interface, the system integration and the development of several applications of the robot-assisted diagnostic ultrasound interface. It also makes a first attempt at comparing the robot-assisted approach with the conventional ultrasound examination through presenting the results of a human factors study. Ultrasound image features selected by the operator are recognized and tracked in realtime using a Correlation algorithm, a Sequential Similarity Detection algorithm, a Star algorithm, a Star-Kalman algorithm, and a Discrete Snakes algorithm. The Sequential Similarity Detection and the Star-Kalman algorithms have excellent performance while tracking features with motions of up to 25 mm/s (200 pixels/s); however, the Star-Kalman algorithm requires 60% less computation time. The Correlation and the Star algorithms exhibit poorer performance and have higher computational costs. The Snake algorithm is unable to track features with motions faster than 12 mm/s (100 pixels/s). All these methods have been compared for carotid artery tracking in ultrasound images over 10 second (300 frames) time periods. Based on feature tracking, ultrasound image servoing in three axes has been incorporated into the ultrasound robot interface and can be enabled to automatically compensate for unwanted motions in the plane of the ultrasound beam. The accuracy of the system is illustrated through a 3-D reconstruction of an ultrasound phantom and human carotid artery. Its functionality was tested by means of an Internetbased, robot-assisted tele-ultrasound examination conducted in Vancouver from Montreal.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat