Document Type dissertation Author Name Cole, Gregory URN etd-040413-212428 Title Modular MRI Guided Device Development System: Development, Validation and Applications Degree PhD Department Robotics Engineering Advisors Dr. Gregory Scott Fischer, Advisor Michael Gennert, Committee Member Robert Norton, Committee Member Dr. Julie Pilitsis, Committee Member Keywords robot robotics stereotaxy neurosurgery intervention modular surgical robotics MRI Date of Presentation/Defense 2012-09-10 Availability unrestricted
Since the first robotic surgical intervention was performed in 1985 using a PUMA industrial manipulator, development in the field of surgical robotics has been relatively fast paced, despite the tremendous costs involved in developing new robotic interventional devices. This is due to the clear advantages to augmented a clinicians skill and dexterity with the precision and reliability of computer controlled motion. A natural extension of robotic surgical intervention is the integration of image guided interventions, which give the promise of reduced trauma, procedure time and inaccuracies. Despite magnetic resonance imaging (MRI) being one of the most effective imaging modalities for visualizing soft tissue structures within the body, MRI guided surgical robotics has been frustrated by the high magnetic field in the MRI image space and the extreme sensitivity to electromagnetic interference.
The primary contributions of this dissertation relate to enabling the use of direct, live MR imaging to guide and assist interventional procedures. These are the two focus areas: creation both of an integrated MRI-guided development platform and of a stereotactic neural intervention system. The integrated series of modules of the development platform represent a significant advancement in the practice of creating MRI guided mechatronic devices, as well as an understanding of design requirements for creating actuated devices to operate within a diagnostic MRI. This knowledge was gained through a systematic approach to understanding, isolating, characterizing, and circumventing difficulties associated with developing MRI-guided interventional systems. These contributions have been validated on the levels of the individual modules, the total development system, and several deployed interventional devices. An overview of this work is presented with a summary of contributions and lessons learned along the way.
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