AI In Medical Imaging

2 credits - Spring Term

This course offers an introduction to the methods, applications, and translational impact of medical image analysis. Students will explore fundamental principles of image acquisition, preprocessing, segmentation, feature extraction, and machine learning in imaging. The curriculum combines lectures, hands-on computational labs, and discussions of both seminal and contemporary research. Emphasis is placed on methodological innovation, clinical translation, and the ethical dimensions of AI in medical imaging. Through case-based learning and project work, faculty provide mentorship while students actively engage in coding exercises, problem-solving, and group project presentations.

View in Course Catalog 

Faculty

Kun-Hsing Yu, MD, PhD

Kun-Hsing Yu, MD, PhD

Associate Professor of Biomedical Informatics, Harvard Medical School

Assistant Professor of Pathology, Brigham and Women's Hospital

Instructor in Epidemiology, Harvard T.H. Chan School of Public Health

Yu Lab

Spring 2026

Schedules for classes in Spring 2026 will be published in Fall 2025.

Cross-Registration

Registration for HMS courses is not available until January. Students who are not in the Master of Medical Sciences in Biomedical Informatics program who wish to cross-register for this course must submit a petition in my.harvard that summarizes their interest in the course and how they have satisfied the prerequisites. 

Cross-reg petitions will be reviewed on a first-come, first-served basis on a date TBD in January 2026. Students can and should submit petitions before this date, but they will not be approved ahead of time. 

For questions about BMI 707 cross-registration, please contact mbi@hms.harvard.edu with the subject line "BMI 707 cross-registration".