MRI Courses on Campus

Introduction to Medical Diagnostic Imaging

Course Number: HSCI 570
Credits: 3
Offered in: Spring
Instructor: Keith Stantz
Intro on the course: This course teaches the fundamentals of medical imaging, including the basic physics and engineering associated with each imaging modality (CT, MRI, PET, and ultrasound), as well as mathematics and computational tools associated with image reconstruction and image processing. The course is intended for students in health sciences, biomedical engineering, physics, and life sciences.

Basics of MR Spectroscopy

Course NumberHSCI 590 
Credits: 3
Weeks: 15
Offered in: Spring
InstructorUlrike Dydak
Intro on the course: This course gives an introduction to the theory, practical aspects and applications of Magnetic Resonance Spectroscopy. It aims at graduate students from all backgrounds, who want to use MRS for their research purposes, however having taken a prior or concurrent course on MRI is of advantage. Topics covered are basics of MRS, localization and suppression techniques, spectroscopic imaging, multinuclear spectroscopy, processing and quantification approaches and spectral editing.The course includes 2 hands-on projects (phantom and in vivo) at the scanner during class time.

fMRI Design and Analysis

Course Number: PSY 629
Credits: 3
Offered in: Alternates annually between Fall & Spring. Spring 2018, Fall 2019, Spring 2020, Fall 2021, etc.
Instructor: Sebastien Helie
Intro on the course: The goal of this course is to introduce students to the design of fMRI experiments and fMRI data analysis using both lectures and hands-on exercises. Covered topics include a short introduction to MR physics, block designs, rapid{event related designs, data preprocessing, and standard analyses using the general linear model. Advanced analysis techniques (e.g., functional connectivity analysis, multivariate pattern analysis, etc.) and common pitfalls in design and analysis will also be covered.

Magnetic Resonance Imaging Theory

Course Number: BME 595
Credits: 3
Offered in: Spring
Instructor: Joseph Rispoli
Intro on the course: This course is an introduction to the theory and design of magnetic resonance imaging systems, with an emphasis on theory from a physics perspective. Mathematical derivations of fundamental principles will be explored. Topics include image acquisition and reconstruction, mechanisms for image contrast and resolution, and an overview of system design, including magnets, gradients, and radiofrequency coils.

Functional MRI Applications

Course Number: BME 595
Credits: 1
Weeks: 8
Offered in: Spring
Instructors: Craig J Goergen, Thomas M Talavage, and Gregory Tamer
Intro on the course: This course covers basic theory and practical training for magnetic resonance imaging. Students will gain hands-on experience with, and work to become independent operators on, the GE 3T Discovery 750 and the Bruker 7T. Weekly lectures will be provided on a wide range of applied and relevant topics, including image formation and contrast, pulse sequence basics, artifacts, advanced sequences, and safety. Weekly labs will allow students to directly train on animal and human systems. The course is ideally designed for students who want to make use of MRI to advance their research.
Necessary background: No course requirements, but a general physics knowledge and technical background is preferred. Instructor permission is required for registration.

MRI QA Internship  

Course Number: HSCI 672
Credits: 3 
Offered in: Fall
Instructor: Ulrike Dydak, Xiaopeng Zhou, Nathan
Intro on the course: This internship course provides didactic training and practical experience in clinical diagnostic medical physics. Students will spend 3-4 hours per week learning the responsibilities of a medical physicist in MRI quality assurance (QA) such as MRI system performance testing, setting up weekly MRI QA procedures, analysis of MRI QA data, and annual clinical system evaluations.
Prerequisites: Primary operator status on an MRI scanner at Purdue or IU; basic knowledge of MRI physics.
Please note:
- Due to the internship character, this course is restricted to very few students and requires instructor permission.

Advanced Data Acquisition and Image Reconstruction Methods in MRI

Course Number: HSCI 590
Credits: 3 
Offered in: Fall
Instructor: Uzay Emir
Intro on the course: This course is intended to teach the most advanced MRI methods that have been used for active areas of MRI research including diffusion, perfusion, functional, spectroscopy, and x-nuclei MRI. The development of algorithms plays an important role in this course. Thus, participants should have established programming skills in C++ and/or Matlab and/or Python. Furthermore, it is advantageous for participants to have attended lectures on image processing or pattern recognition of MRI. An introduction into softwares and MRI basics will be given at the beginning of the course.

Fundamentals of NMR spectroscopy

Course Number: CHM 615
Credits: 3
Offered in: Every other Spring
Instructor: Nikolai Skrynnikov
Intro on the course: The course is intended to provide in-depth coverage of fundamental concepts in modern NMR spectroscopy. Included are the vector model of spin resonance, topics in signal processing, product operator formalism, discussion of important 2D experiments, Redfield relaxation theory, and methods for molecular structure determination. The emphasis is on general spectroscopic concepts, also used outside spin resonance spectroscopy. Spectrometer operation and data processing are also demonstrated. 
Prerequisites: undergraduate degree or completed advanced coursework in chemistry, physics, biology, or engineering. Basic knowledge of NMR is expected, but not required.

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