Klaas P. Prüssmann: Catalogue data in Autumn Semester 2022

Name	Prof. Dr. Klaas P. Prüssmann
Field	Bioimaging
Address	Inst. f. Biomedizinische Technik ETH Zürich, ETZ F 89 Gloriastrasse 35 8092 Zürich SWITZERLAND
Telephone	+41 44 632 66 96
Fax	+41 44 632 13 02
E-mail	pruessmann@biomed.ee.ethz.ch
Department	Information Technology and Electrical Engineering
Relationship	Full Professor

Number

Title

ECTS

Hours

Lecturers

227-0085-53L

Projects & Seminars: Motion Sensing Technologies for Magnetic Resonance Imaging (MRI)

Does not take place this semester.
Only for Electrical Engineering and Information Technology BSc.

Course can only be registered for once. A repeatedly registration in a later semester is not chargeable.

4 credits

K. P. Prüssmann

Abstract

The category of "Laboratory Courses, Projects, Seminars" includes courses and laboratories in various formats designed to impart practical knowledge and skills. Moreover, these classes encourage independent experimentation and design, allow for explorative learning and teach the methodology of project work.

Learning objective

Current MRI scans are limited by patient motion. In clinics, radiologists are often confronted with images with severe motion artefacts in their images. They either have to make a diagnosis although the image artefacts were they could miss crucial information, or they have to send the patient back into the scanner for reacquisition. Such reacquisition might inflict additional costs in the six-figure range per scanner per year.
Further, in research, MRI images from ultra-high field systems are already limited by motion from the cardiobalistic and respiratory movement. Resulting in subpar performance if not addressed appropriately.

The key to overcoming such motion artefacts is estimating the motion and correct for it. Preferably this is done prospective in real-time or otherwise afterwards retrospective in the image reconstruction. Such methods are instrumental in brain imaging since the brain's movement is well described by the rigid body behaviour of the skull.

To do such motion correction, one needs a motion-sensing technology to measure the movement of the human skull with high precision, accuracy and temporal resolution. All this has to be done while being integrated into an MRI machine where powerful static magnetic fields are present, kW of pulsed RF power and MVA of changing magnetic field gradients are present.

In this P&S we explore different motion sensing technologies suitable for deployment in an MRI machine. What you can expect is that we discuss the theory of multiple sensing technologies and then implement an optical, shortwave RF and NMR phase motion sensor. We will spend most of our time in the lab constructing such sensors and testing them on our robotic test bench. Finally, we would also experiment in our MRI facilities, where we would perform motion correction experiments.

227-0385-10L

Biomedical Imaging

6 credits

S. Kozerke, K. P. Prüssmann

Abstract

Introduction to diagnostic medical imaging based on electromagnetic and acoustic fields including X-ray planar and tomographic imaging, radio-tracer based nuclear imaging techniques, magnetic resonance imaging and ultrasound-based procedures.

Learning objective

Upon completion of the course students are able to:

• Explain the physical and mathematical foundations of diagnostic medical imaging systems
• Characterize system performance based on signal-to-noise ratio, contrast-to-noise ratio and transfer function
• Design a basic diagnostic imaging system chain including data acquisition and data reconstruction
• Identify advantages and limitations of different imaging methods in relation to medical diagnostic applications

Content

• Introduction (intro, overview, history)
• Signal theory and processing (foundations, transforms, filtering, signal-to-noise ratio)
• X-rays (production, tissue interaction, contrast, modular transfer function)
• X-rays (resolution, detection, digital subtraction angiography, Radon transform)
• X-rays (filtered back-projection, spiral computed tomography, image quality, dose)
• Nuclear imaging (radioactive tracer, collimation, point spread function, SPECT/PET)
• Nuclear imaging (detection principles, image reconstruction, kinetic modelling)
• Magnetic Resonance (magnetic moment, spin transitions, excitation, relaxation, detection)
• Magnetic Resonance (plane wave encoding, Fourier reconstruction, pulse sequences)
• Magnetic Resonance (contrast mechanisms, gradient- and spin-echo, applications)
• Ultrasound (mechanical wave generation, propagation in tissue, reflection, transmission)
• Ultrasound (spatial and temporal resolution, phased arrays)
• Ultrasound (Doppler shift, implementations, applications)
• Summary, example exam questions

Lecture notes

Lecture notes and handouts

Literature

Webb A, Smith N.B. Introduction to Medical Imaging: Physics, Engineering and Clinical Applications; Cambridge University Press 2011

Prerequisites / Notice

Analysis, Linear algebra, Physics, Basics of signal theory, Basic skills in Matlab/Python programming

Competencies

Subject-specific Competencies	Concepts and Theories	assessed
	Techniques and Technologies	assessed
Method-specific Competencies	Analytical Competencies	assessed
	Decision-making	fostered
	Media and Digital Technologies	fostered
	Problem-solving	assessed
Social Competencies	Communication	assessed
	Cooperation and Teamwork	assessed
Personal Competencies	Adaptability and Flexibility	fostered
	Creative Thinking	assessed
	Critical Thinking	assessed
	Integrity and Work Ethics	fostered
	Self-direction and Self-management	fostered