Master of Science in Imaging Science

The McKelvey School of Engineering offers a unique interdisciplinary master of science in imaging science program that prepares graduates for success in industry or to advance to doctoral studies.

Students will be taught and mentored by faculty from departments and programs throughout Washington University in St. Louis, including Biomedical Engineering, Electrical & Systems Engineering, Computer Science & Engineering, Mechanical Engineering & Materials Science and the School of Medicine. 

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.

Degree requirements

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.

Required core imaging science courses (13 credit hours)

Mathematics and physics of imaging modalities courses (must complete two from this list):

• BME 570 CSE/ESE 5931: Mathematics of Imaging Science (three credit hours)
• BME 591: Biomedical Optics I: Principles (three credit hours)
• BME 594: Ultrasound Imaging (three credit hours)
• ESE 582/BME 5820: Fundamentals and Applications of Modern Optical Imaging (three credit hours)
• ESE/BME 589: Biological Imaging Technology (three credit hours)

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):

• BME 544: Biomedical Instrumentation (three credit hours)
• BME 592: Biomedical Optics 2: Advanced Topics in Biophotonics (three credit hours)
• CSE 559A: Computer Vision (three credit hours)

Seminar course:

• ESE 596/BME 506: Seminar in Imaging Science and Engineering (one credit hour)

Additional electives (may choose from the list below and above to meet the 30 units required):

• BIOL 5146: Principles and Applications of Biological Imaging (three credit hours)
• BIOL 5147: Contrast Agents for Biological Imaging (three credit hours)
• BME 500: Independent Study (three credit hours)
• BME 599: Master Research (six credit hours)
• ESE 438/538A: Applied Optics (three credit hours)
• ESE 520: Probability and Stochastic Processes (three credit hours)
• ESE/BME 5933: Theoretical Imaging Science (three credit hours)
• ESE 5934: Practicum in Imaging Science (three credit hours)
• CLNV 510: Ethical and Legal Issues in Clinical Research (three credit hours)