WashU has a long history as a leading institution in imaging science research, with hundreds of expert faculty researching sensors, physical and mathematical modeling, image representation, algorithm development, deep learning methods, artificial intelligence, performance quantification, computational implementations and implementations of imaging systems. McKelvey Engineering aims to equip graduates with practical application skills and the physical and mathematical foundations of engineering principles and imaging sciences.
The master of science in imaging science requires 30 unit hours, including 13 credit hours from the core list (two mathematics and physics courses, one seminar course, and one computation and one application course each selected from the list below) and the remaining credits from the electives list.
Computational imaging courses (must complete one from this list): Due to the partial overlap between ESE 417 Introduction to Machine Learning and Pattern Classification and CSE 417T Introduction to Machine Learning, it is recommended that students take only one, as only one of these courses can count towards the curriculum requirements.
ESE 415: Optimization (three credit hours)
ESE 417: Introduction to Machine Learning and Pattern Classification (three credit hours)
ESE 5932: Computational Imaging Science (three credit hours)
CSE 417T: Introduction to Machine Learning (three credit hours)
CSE 515T: Bayesian Methods in Machine Learning (three credit hours)
CSE 517A: Machine Learning (three credit hours)
Imaging applications courses (must complete one from this list):
ESE 5934: Practicum in Imaging Science (three credit hours)
CLNV 510: Ethical and Legal Issues in Clinical Research (three credit hours)
PhD in Imaging Science
WashU offers one of only two doctoral degree programs in imaging science in the United States. Our interdisciplinary curriculum focuses on the technology of imaging with applications ranging from cancer diagnosis to virtual reality.