227-0385-10L  Biomedical Imaging

SemesterHerbstsemester 2022
DozierendeS. Kozerke, K. P. Prüssmann
Periodizitätjährlich wiederkehrende Veranstaltung

KurzbeschreibungIntroduction 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.
LernzielUpon 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
Inhalt• 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
SkriptLecture notes and handouts
LiteraturWebb A, Smith N.B. Introduction to Medical Imaging: Physics, Engineering and Clinical Applications; Cambridge University Press 2011
Voraussetzungen / BesonderesAnalysis, Linear algebra, Physics, Basics of signal theory, Basic skills in Matlab/Python programming
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Verfahren und Technologiengeprüft
Methodenspezifische KompetenzenAnalytische Kompetenzengeprüft
Medien und digitale Technologiengefördert
Soziale KompetenzenKommunikationgeprüft
Kooperation und Teamarbeitgeprüft
Persönliche KompetenzenAnpassung und Flexibilitätgefördert
Kreatives Denkengeprüft
Kritisches Denkengeprüft
Integrität und Arbeitsethikgefördert
Selbststeuerung und Selbstmanagement gefördert