Studentenprojekte

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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

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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... 

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

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