The McKelvey School of Engineering offers an interdisciplinary Master of Science in Imaging Science that prepares graduates for success in industry or to further advance their study at the doctoral level.

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

WashU is a long-term leader 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's degree in imaging science requires 30 unit hours, including 13 unit 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):

  • ESE 415: Optimization (three credit hours)
  • ESE 419: Special Topics in Optimization and Learning: 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/BME 596: 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)