Impact of deep learning architectures on accelerated cardiac T1 mapping using MyoMapNet

The objective of the current study was to investigate the performance of various deep learning (DL) architectures for MyoMapNet, a DL model for T1 estimation using accelerated cardiac T1 mapping from four T1‐weighted images collected after a single inversion pulse (Look‐Locker 4 [LL4]). We implement...

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Bibliographic Details
Published in:	NMR in biomedicine Vol. 35; no. 11; pp. e4794 - n/a
Main Authors:	Amyar, Amine, Guo, Rui, Cai, Xiaoying, Assana, Salah, Chow, Kelvin, Rodriguez, Jennifer, Yankama, Tuyen, Cirillo, Julia, Pierce, Patrick, Goddu, Beth, Ngo, Long, Nezafat, Reza
Format:	Journal Article
Language:	English
Published:	Oxford Wiley Subscription Services, Inc 01.11.2022
Subjects:	Accuracy Artificial neural networks Biological products cardiac MRI Coders Data collection Deep learning Heart Image quality Inversion inversion‐recovery cardiac T1 mapping Mapping myocardial tissue characterization Myocardium Neural networks Performance evaluation Training
ISSN:	0952-3480, 1099-1492, 1099-1492
Online Access:	Get full text
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