3 March 2017 Monitoring electromagnetic tracking error using redundant sensors
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Abstract
PURPOSE: The intraoperative measurement of tracking error is crucial to ensure the reliability of electromagnetically navigated procedures. For intraoperative use, methods need to be quick to set up, easy to interpret, and not interfere with the ongoing procedure. Our goal was to evaluate the feasibility of using redundant electromagnetic sensors to alert users to tracking error in a navigated intervention setup. METHODS: Electromagnetic sensors were fixed to a rigid frame around a region of interest and on surgical tools. A software module was designed to detect tracking error by comparing real-time measurements of the differences between inter-sensor distances and angles to baseline measurements. Once these measurements were collected, a linear support vector machine-based classifier was used to predict tracking errors from redundant sensor readings. RESULTS: Measuring the deviation in the reported inter-sensor distance and angle between the needle and cautery served as a valid indicator for electromagnetic tracking error. The highest classification accuracy, 86%, was achieved based on readings from the cautery when the two sensors on the cautery were close together. The specificity of this classifier was 93% and the sensitivity was 82%. CONCLUSION: Placing redundant electromagnetic sensors in a workspace seems to be feasible for the intraoperative detection of electromagnetic tracking error in controlled environments. Further testing should be performed to optimize the measurement error threshold used for classification in the support vector machine, and improve the sensitivity of our method before application in real procedures.
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Vinyas Harish, Vinyas Harish, Eden Bibic, Eden Bibic, Andras Lasso, Andras Lasso, Matthew S. Holden, Matthew S. Holden, Thomas Vaughan, Thomas Vaughan, Zachary Baum, Zachary Baum, Tamas Ungi, Tamas Ungi, Gabor Fichtinger, Gabor Fichtinger, } "Monitoring electromagnetic tracking error using redundant sensors", Proc. SPIE 10135, Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling, 101352R (3 March 2017); doi: 10.1117/12.2256004; https://doi.org/10.1117/12.2256004
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