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TU Berlin

Inhalt des Dokuments

Magnetic Resonance Imaging (I+II)

Dozent:
Prof.Dr. T. Schaeffter
Angeboten im:
Winter semester (Part I) Summer semster (Part II)
Termin:
Wednesday 10:00-12:00
Raum:
SG09-215

Learning Outcomes

The course is held by Prof. Dr. Tobias Schaeffter Head of Division, Medical Physics and Metrological Information Technologies at the PTB Berlin.


MRI I (winter):

Participants will learn the basic principles and the instrumentation of magnetic resonance imaging (MRI). Basic measurement techniques (MR-sequences) and the related image contrast mechanisms will be studied. The mathematical framework is developed to describe image encoding, the point-spread function (PSF), signal-to-noise ratio and contrast mechanism of MRI. Matlab exercises and homework are used to deepen the understanding of the basic concepts.


MRI II (summer):

This course is geared towards master students and PhD students who have visited the magnetic resonance imaging (MRI) course or have basic knowledge of MRI. The participants will learn concepts of advanced MRI encoding and decoding strategies. In particular the mathematical frameworks are developed to solve the inverse problem of fast acquisition strategies. The participants will also learn about quantitative MRI techniques and related data analysis techniques Matlab exercises and homework are used to deepen the understanding of the concepts.

 

 

Content

MRI I (winter):

History of MRI, physical principle, Nuclear Magnetic Resonance (NMR) Effect, relaxation phenomena and chemical shift, spatial localisation and imaging, k-space formalism, basic pulse sequences (gradient and spin echo), contrast manipulation, fast imaging sequences, motion compensation, instrumentation and safety, signal-to-noise ratio, image-quality, artefacts, clinical applications and research.


MRI II (summer):

MRI signal equation, direct Fourier reconstruction, advanced k-space trajectories and gridding reconstruction, parallel imaging, compressed sensing, RF-pulse design and two-dimensional excitation, quantitative MRI (flow, diffusion, relaxation time mapping), cardiac MRI.

Further information

Description of Teaching and Learning Methods

MRI I:
The lecture will provide physical and mathematical background to understand the principles of MRI. Participants are expected to rehearse the content after class in preparation for exercises. The exercises focus on the calculation of practical questions and exercises at the computer. For this, matlab-code will be made available, which need to be modified. Homework will consist of specific tasks with calculations and programming solutions using matlab. The participants will also attend a MR-measurement session.

MRI II:

The lecture will provide theoretical background to understand advanced encoding and decoding strategies in MRI. Furthermore, biophysical properties and related quantitative MR-measurements will be introduced. Participants are expected to rehearse the content after class in preparation for exercises. The exercises focus on the calculation of practical questions and exercises at the computer. For this, matlab-code will be made available, which need to be modified. Homework will consist of specific tasks with calculations and programming solutions using matlab. The participants will attend a MR-measurement session.

Workload and Credit Points

The workload in total is 180 hours, this is equivalent to 6 LP (1LP for 30 hours of work).

Module completion

The module will be completed with Portfolio examination with 100 points in total which will be shared by homework, a written examination and an oral examination.

 

Requirements for participation and examination

Desirable prerequisites for participation in the courses:
Mathematical background at the level of MS students in Engineering (Fourier transforms, signals and systems, linear algebra and notions of matrix theory). Knowledge of basic Matlab functionality is helpful The course is open to students enrolled in any MSc in Electrical Engineering, Mathematics and Physics


Registration Procedures

Please sign up for this course in ISIS after the first week of the new semester.

Zusatzinformationen / Extras

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