Magnetic Tracking Sensors for Open Surgery Evaluation, Ultrasound Multi-view Fusion, and Cardiac Modeling

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We would like to purchase one new magnetic tracking system which can accommodate a 16-sensor unit with an outer diameter of 1.5 mm to be used for two of the three projects, and a second 16-sensor unit with an outer diameter of 0.58 mm for the cardiac modeling project. The first project is a sensor-based open surgery activity analysis project where two instrumented surgical gloves will be used in order to record expert surgeons' performances during open surgical procedures and to compare their performance with those of novices during training. Our goal is to insert into two modified surgical gloves, ten small (~1.5 mm) magnetic sensors combined with strain gage sensors to measure the position of each finger in 6-D (position and orientation) and the forces applied to them. The use of a magnetic tracker is critical as methods that rely on a direct line of sight are impossible to use in open surgery due to visual occlusions. Once the data is acquired for various tasks, our goal is to use global features and a simple curvature/force correlation technique to perform a comparison to determine how close the performances of the trainees and the expert surgeons are. In the second project, we propose a method that relies on the same portable 6-D magnetic tracking system mounted on an ultrasound scanner (US) to perform image alignment. This tracking system will allow us to solve image alignment as it eliminates the constraints on image overlap and quality as the accuracy of the alignment obtained by the tracking system is far superior to the image resolution of a US sensor. In the third project, we are planning to use the same equipment but with smaller magnetic trackers (0.58 mm) to validate patient specific models of a heart and to extract dynamic model parameters by measuring live heart motion. The main idea is to use those sensors to track the position of key anatomical landmarks on the heart and then compare them with our simulation. The discrepancy will then be minimized by adjusting model parameters such as geometry and material properties which are difficult to evaluate ex-vivo.