Cardiovascular Magnetic Resonance

Open Opportunities

Contactless Fiber-Optic Photoplethysmography-based Gating for MRI ETH Zurich Cardiovascular Magnetic Resonance This project aims to collect diverse forehead PPG datasets using a newly developed device, to evaluate variability across populations and sensor placements and, to explore their impact on signal quality. You will apply classical signal processing and machine learning methods to extract reliable MRI triggers from the PPG signal to statistically quantify the pulse arrival time (PAT) and its variability. If time permits, you may further investigate the extraction of respiratory-modulated components from the PPG waveform. Artificial Intelligence and Signal and Image Processing, Biomechanical Engineering, Electrical Engineering, Optometry Bachelor Thesis, Semester Project

In-silico cardiac and cardiovascular modelling with physics informed neural networks ETH Zurich Cardiovascular Magnetic Resonance The aim of the project is to investigate the benefits, requirements and drawbacks of physics informed neural networks in the context of personalised cardiac and cardiovascular models Biomechanical Engineering, Clinical Engineering, Computation Theory and Mathematics, Fluidization and Fluid Mechanics, Neural Networks, Genetic Alogrithms and Fuzzy Logic, Simulation and Modelling Master Thesis

Generation of synthetic cardiac phantoms for healthy and pathological anatomy and function using generative AI ETH Zurich Cardiovascular Magnetic Resonance The project focuses exploiting generative AI to build synthetic numerical phantom for cardiac anatomy and function suitable for representing population variability. Biomechanical Engineering, Information, Computing and Communication Sciences Master Thesis