Project Description
Ultrasound imaging is an important tool for medical diagnostics, but we must work to develop imaging sequences that can image faster and with greater clarity to address a wider range of patients and clinical tasks. We have developed a method that involves transmitting from each element on an ultrasound array multiple times using time delays and weightings as an encoding. We then decode the echoes we receive to form a high quality image. The student in this project will apply numerical optimization methods previously developed by a PhD student to select the best parameters for imaging. The student will work in the lab to verify numerical solutions using our programmable research ultrasound machine and imaging phantoms. The student will learn skills in numerical optimization, ultrasound simulation, and experimental ultrasound methods using a research scanner.
Special Requirement
Some proficiency in programming (Matlab and Python preferred)
Contact
- Nick Bottenus (faculty)
- Stephen Becker (faculty)