Magnetic resonance imaging (MRI) is a safe and non-invasive medical imaging modality that incorporates all facets of engineering. This course provides an introduction to MRI, particularly focusing on computational co-design of the signal acquisition and post-processing algorithms. The course will cover the principles of MRI, including basic system hardware, spin physics, signal formation, contrast mechanisms, pulse sequence design, image detection, and image reconstruction. Advanced image reconstruction topics will be discussed including parallel imaging, compressed sensing, and machine learning. Concepts will be explored through the use of real and synthetic data in the homeworks, labs, and final project.
The course will consist of lectures on the board/tablet as well as Python live demos.
The online class system is hosted on Canvas: [Canvas Course Page]
Handouts will be distributed there. We will also use Canvas to send group e-mails and do online grading. Please make sure you know how to access Canvas and that you are listed there as a student.
We will also use Piazza for online discussions: [Piazza Course Page]
This is a good place to post questions, which can be answered by the instructor, TA, or other students. Since students often have related questions, this is also a good place to look to see other questions and answers.
Assignments and exams will be graded using Gradescope: [Gradescope Course Page]
Gradescope allows the course instructors to quickly grade and return your work in a timely manner.
Links to Piazza and Gradescope are also available through the Canvas course page.
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