Computational Methods for Medical Imaging

Lecture, four hours; discussion, two hours; outside study, six hours. Requisites: course 32 or Program in Computing 10C with grade of C- or better, Mathematics 33A, one course from Civil and Environmental Engineering 110, Electrical and Computer Engineering 131A, Mathematics 170A, 170E, or Statistics 100A. Theory and practice of image acquisition including angiography, computed tomography (CT), and magnetic resonance (MR). Project-based course covers applied topics in medical imaging including image processing, atlasing, predictive modeling, personalized medicine, data driven and machine learning methods. Letter grading.

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Course

Instructor
Fabien Scalzo
Previously taught
20S 19S 18S