Type of Document Dissertation Author Pheiffer, Thomas Steven URN etd-06092014-133155 Title Surgical Navigation Using Tracked Ultrasound Degree PhD Department Biomedical Engineering Advisory Committee
Advisor Name Title Michael I. Miga Committee Chair Benoit Dawant Committee Member Bob Galloway Committee Member Brett Byram Committee Member Reid Thompson Committee Member Keywords
- image-guided surgery
- finite element modeling
Date of Defense 2014-06-04 Availability unrestricted AbstractUltrasound is an imaging modality which provides spatial measurements of subsurface targets during surgical interventions without the radiation or logistical concerns of CT or MR imaging, respectively. However, image interpretation is known to be a challenging task without other sources of information. This is not only because of the noise characteristics of ultrasound, but also because manipulation and compression of soft tissue during imaging with an ultrasound probe can distort the size and position of targets. A system for tracking ultrasound images in 3D space was implemented with a novel framework for addressing these issues.
A novel laser range scanner was first characterized with respect to its ability to create textured point clouds tracked in physical space. The geometric point cloud accuracy was determined using phantoms to be submillimetric, and the tracking accuracy of the system was found to be similar to other passive optical tracking tools. This study established a gold standard registration and surface measurement tool to be used in the tracked ultrasound framework.
A strategy was developed for correcting tissue compression by using the pose of the ultrasound probe within the tissue. An initial image-to-physical registration of the tracked ultrasound to a patient-specific model was done to calculate this pose. After registration, the pose of the probe was used to assign boundary conditions to the tissue model. The solution of the model was then reversed to estimate the tissue in the uncompressed state. This strategy was found to be capable of reducing errors of approximately 1 cm to 2-3 mm.
The correction strategy was then generalized to use a block mesh calibrated to the tip of the ultrasound probe. This strategy did not require a patient-specific mesh, and only required an intraoperative measurement of compression depth. The formulation of the generic model was also significantly faster than the patient-specific method and gave nearly the same correction accuracy. Future work will involve incorporation of accurate material properties into the model correction, as well as real-time surface point cloud information from stereovision cameras.
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