Principles of Magnetic Resonance Imaging
Fundamentals of MRI including signal-to-noise ratio, resolution, and contrast as dictated by physics, pulse sequences, and instrumentation. Image reconstruction via 2D FFT methods. Fast imaging reconstruction via convolution-back projection and gridding methods and FFTs. Hardware for modern MRI scanners including main field, gradient fields, RF coils, and shim supplies. Software for MRI including imaging methods such as 2D FT, RARE, SSFP, spiral and echo planar imaging methods.
Topics
- Graduate level understanding of physics, hardware, and systems engineering description of image formation, and image reconstruction in MRI. Experience in Imaging with different MR Imaging systems. This course should enable students to begin graduate level research at Berkeley (Neuroscience labs, EECS and Bioengineering), LBNL or at UCSF (Radiology and Bioengineering) at an advanced level and make research-level contribution
Official catalogue course objectives and student learning outcomes
Prerequisites & course information
{'preRequisiteCourse': '1242582', 'concurrentPrerequisit': False}; {'preRequisiteCourse': '1242581', 'concurrentPrerequisit': False}; {'preRequisiteCourse': '1062941', 'concurrentPrerequisit': False}; {'preRequisiteCourse': '1244721', 'concurrentPrerequisit': False}; {'preRequisiteCourse': '1244722', 'concurrentPrerequisit': False}
Sources
- Course catalogue ↗2026-2027