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17 March 2008 Evaluation of motion compensation approaches for soft tissue navigation
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Abstract
Organ motion was quantified and motion compensation strategies for soft-tissue navigation were evaluated in a porcine model. Organ motion due to patient repositioning, and respiratory motion during ventilated breathing were quantified. Imaging was performed on a 16-slice CT scanner. Organ motion due to repositioning was studied by attaching 7 external skin fiducials and inserting 7 point fiducials in the livers of ventilated pigs. The pigs were imaged repeatedly in supine and decubitus positions. Registrations between the images were obtained using either all external fiducials or 6 of the 7 internal fiducials. Target registration errors (TRE) were computed by using the leave-one-out technique. Respiratory organ motion was studied by inserting 7 electromagnetically (EM) tracked needles in the livers of 2 pigs. One needle served as primary target, the remaining six served as reference needles. In addition, 6 EM tracked skin fiducials, 5 passive skin fiducials, and one dynamic reference tracker were attached. Registrations were obtained using three different methods: Continuous registration with the tracking data from internal and external tracked fiducials, and one-time registration using the passive skin fiducials and a tracked pointer with dynamic reference tracking. The TRE for registering images obtained in supine position after an intermittent decubitus position ranged from 3.3 mm to 24.6 mm. Higher accuracy was achieved with internal fiducials (mean TRE = 6.4 mm) than with external fiducials (mean TRE = 16.7 mm). During respiratory motion, the FRE and TRE were shown to be correlated and were used to demonstrate automatic FRE-based gating. Tracking of target motion relative to a reference time point was achieved by registering nearby reference trackers with rigid and affine transformations. Linear motion models based on external and internal reference trackers were shown to reduce the target motion by up to 63% and 90%, respectively.
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Jochen Krücker, Sheng Xu, Neil Glossop, William F. Pritchard, John Karanian, Alberto Chiesa, and Bradford J. Wood "Evaluation of motion compensation approaches for soft tissue navigation", Proc. SPIE 6918, Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling, 691814 (17 March 2008); doi: 10.1117/12.771040; https://doi.org/10.1117/12.771040
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