MRI Data Acquisition

Principles and techniques of MRI data acquisition, providing students with essential knowledge and hands-on skills

Course details
Non-credit course
University
Boğaziçi Üniversitesi
Institution
Teacher
Various Teachers
Category
Clinical Neurotechnology
Dimension
Clinical neurotechnology
Level
Advanced

This course focuses on the principles and techniques of MRI data acquisition, providing students with essential knowledge and hands-on skills. Through eleven expert-led lectures by Matthias Günther, Daniel Honkiss, and Jörn Huber,  participants will gain insight into the concept of MR sequence development, k-space, and MR image reconstruction. The course also covers parallel and dynamic imaging techniques, modern AI-enhanced methods, and MR artefacts. By the end of the course, participants will have a clearer understanding of what an MR sequence is, concepts of k-space, and MR image reconstruction. By the end of the course, participants will be equipped to understand and apply key MRI acquisition techniques in practice. 

This course collection is offered as part of the TACTIX project in collaboration with Boğaziçi University, Amsterdam UMC and Fraunhofer MEVIS.

Target Audience: MSc and PhD students who are interested in learning the main methods of MRI data acquisition

Prerequisites

Basic knowledge of human anatomy and familiarity with medical imaging concepts; prior experience with CT or MRI interpretation is beneficial but not mandatory.

Course Features
Understand the concept of k-space and its role in MRI image reconstruction.
Learn the fundamentals of MR sequences and explore advanced sequences to enhance image quality.
Understand EPI and GRASE sequences for functional and structural imaging applications.
Explore compressed sensing to improve image quality and reduce scan times.
Apply AI-enhanced methods for image reconstruction and analysis.
Learn and apply motion correction techniques to reduce artifacts and improve dynamic imaging.
Identify common MRI artifacts and develop methods to minimize their impact.
Develop skills in sequence programming to create and optimize MRI protocols for various applications.

Lessons

Number of lessons: 2
  •  
    Introduction to gammaStar
    Daniel Hoinkiss

    vendor-independent platform that standardizes MRI sequence development and image reconstruction. The lecture explains how gammaSTAR addresses the heterogeneity of MRI systems (Siemens, Philips, GE) by using a unified description…

  •  
    MRI Artefacts
    Jörn Huber

    This lecture explores common MRI artifacts, explains their mathematical origins using Fourier Transform principles, and provides strategies for mitigation. Key topics include aliasing (wraparound) caused by a small field of view,…