Studentenprojekte
In-silico cardiac and cardiovascular modelling with physics informed neural networks
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
Schlagwörter
cardiac modelling, neural network, in-silico models, personalized medicine, reduced-order modelling, fluid dynamics, continuum mechanics, aortic flow
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Master Thesis
Description
Goal
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Publiziert seit: 2025-01-17 , Frühester Start: 2020-09-01
Organisation(en) Cardiovascular Magnetic Resonance
Host(s) Buoso Stefano , Kozerke Sebastian, Prof
Themen Information, Computing and Communication Sciences , Engineering and Technology
Generation of synthetic cardiac phantoms for healthy and pathological anatomy and function using generative AI
The project focuses exploiting generative AI to build synthetic numerical phantom for cardiac anatomy and function suitable for representing population variability.
Schlagwörter
Generative models, deep learning, phantoms, variational autoencoders, cardiac mechanics, cardiac function, simulation
Labels
Master Thesis
Description
Goal
Contact Details
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Dieses Projekt öffnen... call_made
Publiziert seit: 2025-01-17 , Frühester Start: 2023-07-01
Organisation(en) Cardiovascular Magnetic Resonance
Host(s) Buoso Stefano , Kozerke Sebastian, Prof
Themen Information, Computing and Communication Sciences , Engineering and Technology