Principles of MRI

Spring 2023

Course Description

This class aims to teach the basic principles of MRI.

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. Fundamental tradeoffs of tailoring hardware and pulse sequences to specific applications. The modern MRI toolbox will be introduced, including selecting a slice or volume, fast imaging methods to avoid image artifacts due to physiologic motion, and methods for functional imaging. The fundamentals of MRI image artifacts (motion, magnetic susceptibility variations, RF field variations) will also be covered. The last part of the class will present emerging research opportunities and concomitant engineering research challenges including high-field MRI, hyperpolarization methods, small animal MRI, cardiac MRI, stem-cell tracking, functional MRI, parallel imaging and compressed-sensing MRI.

Instructor:

Michael (Miki) Lustig

506 Cory Hall(510)643-9338mlustig@eecs.berkeley.edu

Office Hours

Cory 293 M 3:30-4:30

GSIs:

Shreya Ramachandran

Discussion: Wednesday 3:30-4:30pm at Cory 293Office Hours: Thursday 4-5pm at Cory 299shreyar@berkeley.edu

Suma Anand

sanand@berkeley.edu

Required Text

D. Nishimura Principles of Magnetic Resonance Imaging Lulu.com 2010

You can get in paperback($35) and hardcover($45) from http://lulu.com.

(Please don't buy from amazon scammers)

Optional references

Bernstein, King and Zhou, Handbook of MRI Pulse Sequences Elsevier/Wiley, 2004
You can get it from Amazon here. This is an excellent book, which anyone working in MRI will want to have.
Z.-P. Liang, P. Lauterbur, Principles of Magnetic Resonance Imaging: A Signal Processing Perspective, IEEE Press. A link to Amazon Here
Haacke, Brown, Thompson, and Venkatesan, Magnetic Resonance Imaging: Physical Principles and Sequence Design, John Wiley & Sons New York, NY 1999. ISBN: 0-471-35128-8.
Richard B. Buxton, An Introduction to Functional Magnetic Resonance Imaging: Principles and Techniques, ISBN: 0521581133. Publisher: Cambridge University Press.

Grading (subject to change)

Weekly assignments consisting of problem sets and potentially some Python programming. (20%)
Two wet labs (20%)
One midterms towards 2/3 of the semester (30%)
Final project (30%)
No late hw, makeup midterms etc. without prior consent from the instructor.

Labs:

Dry Python assignments, almost weekly.
Lab 1: Wet MRI experiments
Lab 2: Wet MRI experiments

Project:

Lecture Notes:

Intro: Lectures 1+2
Prereq: Lectures 3+4
Chapter 3: Lectures 5+6
Chapter 4: Lectures 6+7
Chapter 5: Lectures 8+
Chapter 6: Lectures 10+
Effects of non-idalities Chapter 7
Imaging considerations Contrast: Contrast
Imaging considerations SNR: SNR

Discussion Notes:

Discussion 1
Discussion 2
Discussion 3 (Slides here)
Discussion 4
Notes (instead of Discussion 5)
Discussion 6
Discussion 7, Additional Notes - Excitation k-space
Discussion 8
Discussion 9
Discussion - 4/12/23

Assignments:

Homework 1 : due Friday, Feb 3rd, 11:59PM
- The LBNL Report 51983, 26-March-2003 by Vitaliy Fadeyev and Carl Haber can be downloaded from here
- Self-grading due Friday, Feb 10th, 11:59PM

Homework 2 : due Friday, Feb 10th, 11:59PM
- Jupyter notebook can be found here. Optional Jupyter notebook can be found here
- Self-grading due Friday, Feb 17th, 11:59PM

Homework 3 : due Friday, Feb 17th, 11:59 PM
- Self-grading due Friday, Feb 24th, 11:59PM

Homework 4 : due Friday, Feb 24th, 11:59PM
- Jupyter notebook can be found here. Instructions for Windows compilation of the Bloch simulator can be found here.
- Self-grading due Wednesday, Mar 8th, 11:59PM

Homework 5 : due Wednesday, Mar 8th, 11:59PM
- Jupyter notebook can be found here and the required spins .h5 file is here.
- Self-grading due Friday, Mar 17th, 11:59PM

Homework 6 : due Friday, Mar 17th, 11:59PM
- Jupyter notebook and data files can be found here
- Self-grading due Friday, Mar 24th, 11:59PM

Homework 7 : due Friday, Mar 24th 11:59 PM
- Jupyter notebook can be found here
- Self-grading due Friday, April 7th, 11:59PM

Homework 8 : due Friday, April 7th, 11:59PM
- Jupyter notebook can be found here and the required spins .h5 file is here.
- Self-grading due Friday, April 21st, 11:59PM

Homework 9 : due Friday, April 21st, 11:59PM
- Jupyter notebook can be found here
- Self-grading due Friday, April 28th, 11:59PM

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