Title: Image Guided High Precision Robotic Positioning in MRI for Medical Applications

Date: Wednesday, August 14

Time: 10:00am-11:00am Eastern time

Location: MRDC 4211

Zoom link: https://gatech.zoom.us/j/99981472542 (Meeting ID: 999 8147 2542)

Daniel Enrique Martinez

Robotics PhD Candidate

Woodruff School of Mechanical Engineering

Georgia Institute of Technology

Committee:

Dr. Jun Ueda (Advisor) – School of Mechanical Engineering, Georgia Institute of Technology

Dr. A-Ping Hu – Food Processing Technology Division, Georgia Tech Research Institute

Dr. John Oshinski – Radiology and Imaging Sciences, Emory University

Dr. F. Levent Degertekin – School of Mechanical Engineering, Georgia Institute of Technology

Dr. Yue Chen – Department of Biomedical Engineering, Georgia Institute of Technology

Abstract:

Magnetic Resonance Imaging (MRI) is a powerful diagnostic tool that offers advanced visualization of human tissue, increasingly used to guide medical procedures such as biopsies and interventions. Nevertheless, navigation in the MRI environment remains challenging due to material, actuator, and sensor restrictions as well as scan time and cost of use. This work presents methods for ensuring high precision robotic positioning in MRI for use in emerging applications through three distinct aims. In the first aim, an MRI-analogous test bench implementing Position Sensitive Devices (PSDs) is established to measure the positioning performance of a previously developed MRI compatible robot, circumventing limitations of MRI resolution and scan time, validating the capability of MRI guided robot navigation methods. In the second aim, the validated high-precision navigation method is leveraged to enable the application of multi-image Super Resolution (SR) algorithms to construct enhanced resolution in-plane MRI slices, leading to improved positioning precision exceeding the limits of the native MRI resolution. In the third aim, a data-based control methodology is developed to compensate for resistive forces when the end-effector of the robotic system is navigating through a complex fluid medium, enabling repeated high accuracy positioning of an acousto-optic sensor inside a gel phantom for measurement and evaluation of radiofrequency induced heating of conductive structures such as medical implants in MRI.