Physics-informed neural networks for myocardial perfusion MRI quantification

R.L.M. van Herten, Amedeo Chiribiri, Marcel Breeuwer, Mitko Veta, Cian Scannell

Research output: Contribution to journal › Article › Academic › peer-review

Keywords

@article{b247e6b6cd9b4793970d031c92f88de1,

title = "Physics-informed neural networks for myocardial perfusion MRI quantification",

keywords = "Physics informed neural networks, myocardial perfusion MRI, small data, tracer-kinetic modelling",

author = "{van Herten}, R.L.M. and Amedeo Chiribiri and Marcel Breeuwer and Mitko Veta and Cian Scannell",

year = "2022",

month = may,

day = "1",

doi = "https://doi.org/10.1016/j.media.2022.102399",

language = "English",

journal = "Medical Image Analysis",

issn = "1361-8415",

publisher = "Elsevier",

}

TY - JOUR

T1 - Physics-informed neural networks for myocardial perfusion MRI quantification

AU - van Herten, R.L.M.

AU - Chiribiri, Amedeo

AU - Breeuwer, Marcel

AU - Veta, Mitko

AU - Scannell, Cian

PY - 2022/5/1

Y1 - 2022/5/1

KW - Physics informed neural networks

KW - myocardial perfusion MRI

KW - small data

KW - tracer-kinetic modelling

U2 - https://doi.org/10.1016/j.media.2022.102399

DO - https://doi.org/10.1016/j.media.2022.102399

M3 - Article

SN - 1361-8415

JO - Medical Image Analysis

JF - Medical Image Analysis

ER -