RI: Medium: Automated Calibration of Ultrasound for Image-Guided Surgical Procedures

Johns Hopkins University, Baltimore MD

Investigators

Abstract

This project, developing advanced mathematical and computational methods for the online calibration of ultrasound probes that takes into account a probabilistic version of the well-known AX = XB sensor-calibration problem that has been overlooked in the robotics and computer vision literature, will advance current capabilities in computer-integrated surgical interventions, leading to lower radiation exposure to patients and better outcomes for minimally-invasive surgery. Ultrasound has many benefits for minimally-invasive surgical procedures, including cost, ease-of-use, and patient/doctor radiation exposure. But ultrasound images are fuzzy and require extensive training for proper use during surgical procedures. As a result, outcomes are heavily dependent on an individual surgeon's skill with the device. Broader Impacts: Beyond the potential benefits to surgical procedures, the Laboratory for Computational Sensing and Robotics (LCSR) at JHU has an established summer program for visiting undergraduate students that will facilitate involvement of undergraduates in the proposed research. In addition, the PI continues to mentor high school students from Baltimore Polytechnic High School through research experiences both during the academic year and the summer. The hands-on and visual nature of ultrasound image acquisition together with the mathematical problems of registration and calibration make this an ideal project to introduce students to the importance of mathematics.