Department of Computer Science at UH

University of Houston

Department of Computer Science

In Partial Fulfillment of the Requirements for the Degree of
Doctor of Philosophy

Junmo An

Will defend his PhD dissertation proposal


Sensors and System Integration for Magnetic Resonance Image (MRI)-Guided and Robot-Assisted Interventions

Abstract

There is an increasing demand for magnetic resonance image (MRI)-guided interventions and robot-assisted surgeries in the field of medical robotics. MRI-guided interventions provide preoperative/intraoperative MR images and intraoperative manipulations. Robot-assisted surgeries guarantee higher safety and great dexterity inside the patient's body. Integration of MRI-guided and robot-assisted intervention techniques bring higher precision, greater dexterity and improved 3D visualization for real-time MR guidance. Despite the potential benefits of these techniques, challenges still remain: (i) for robust localization and fast tracking of MR compatible manipulators, (ii) for adequate characterization of human tissue and multimodality approaches, (iii) for higher flexibility to overcome lack of navigation and limited workspace inside the human body and the MRI scanner.

The goal of this research is to propose an approach for the integration of sensors and manipulators for the MRI-guided and robot-assisted interventions. The specific objectives are: (i) to study robust localization and fast tracking with inductively-coupled radio frequency (ICRF) coils that are optically tuned and detuned by the control of an MR compatible manipulator, (ii) to study manipulator-mounted magnetic resonance spectroscopy (MRS) / light induced fluorescence (LIF) probe for multimodality scanning, (iii) to develop an MR compatible dexterous robotic manipulator for higher flexibility and accessibility, (iv) to integrate the above mentioned techniques for the MRI-guided and robot-assisted interventions.

 

Date: Wednesday, December 4, 2013
Time: 10:00 AM
Place: PGH 550

Faculty, students, and the general public are invited.
Advisor: Prof. Nikolaos V. Tsekos