@inbook{00a61ce17b724b7a81feb2a1bea5284e,
title = "Automatic Myocardial Disease Prediction from Delayed-Enhancement Cardiac MRI and Clinical Information",
abstract = "Delayed-enhancement cardiac magnetic resonance (DE-CMR) provides important diagnostic and prognostic information on myocardial viability. The presence and extent of late gadolinium enhancement (LGE) in DE-CMR is negatively associated with the probability of improvement in left ventricular function after revascularization. Moreover, LGE findings can support the diagnosis of several other cardiomyopathies, but their absence does not rule them out, making disease classification by visual assessment difficult. In this work, we propose deep learning neural networks that can automatically predict myocardial disease from patient clinical information and DE-CMR. All the proposed networks achieved very good classification accuracy (>85%). Including information from DE-CMR (directly as images or as metadata following DE-CMR segmentation) is valuable in this classification task, improving the accuracy to 95–100%.",
keywords = "Cardiac MRI, Classification, Late gadolinium enhancement, Myocardial infarction",
author = "Ana Louren{\c c}o and Eric Kerfoot and Irina Grigorescu and Scannell, {Cian M.} and Marta Varela and Correia, {Teresa M.}",
note = "Funding Information: Acknowledgments. This work was supported by the Wellcome/EPSRC Centre for Medical Engineering [WT 203148/Z/16/Z] and the British Heart Foundation Centre of Research Excellence at Imperial College London [RE/18/4/34215]. Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 11th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2020 held in Conjunction with MICCAI 2020 ; Conference date: 04-10-2020 Through 04-10-2020",
year = "2021",
doi = "10.1007/978-3-030-68107-4_34",
language = "English",
isbn = "9783030681067",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "334--341",
editor = "{Puyol Anton}, Esther and Mihaela Pop and Maxime Sermesant and Victor Campello and Alain Lalande and Karim Lekadir and Avan Suinesiaputra and Oscar Camara and Alistair Young",
booktitle = "Statistical Atlases and Computational Models of the Heart. MandMs and EMIDEC Challenges - 11th International Workshop, STACOM 2020, Held in Conjunction with MICCAI 2020, Revised Selected Papers",
address = "Germany",
}