Impact of deep learning architectures on accelerated cardiac T <sub>1</sub> mapping using MyoMapNet-Reference-Cited by-同舟云学术

Impact of deep learning architectures on accelerated cardiac T ₁ mapping using MyoMapNet

Published:2022-07-14 Issue:11 Volume:35 Page:
ISSN:0952-3480
Container-title:NMR in Biomedicine
language:en
Short-container-title:NMR in Biomedicine

Author:

Amyar Amine¹,Guo Rui¹,Cai Xiaoying¹²,Assana Salah¹,Chow Kelvin³,Rodriguez Jennifer¹,Yankama Tuyen¹,Cirillo Julia¹,Pierce Patrick¹,Goddu Beth¹,Ngo Long¹,Nezafat Reza¹

Affiliation:

1. Department of Medicine (Cardiovascular Division) Beth Israel Deaconess Medical Center and Harvard Medical School Boston Massachusetts USA

2. Siemens Medical Solutions USA, Inc. Boston Massachusetts USA

3. Siemens Medical Solutions USA, Inc. Chicago Illinois USA

Funder

American Heart Association

National Institutes of Health

Publisher

Wiley

Subject

Spectroscopy,Radiology, Nuclear Medicine and imaging,Molecular Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/nbm.4794

Reference28 articles.

1. Accuracy, Precision, and Reproducibility of Four T1 Mapping Sequences: A Head-to-Head Comparison of MOLLI, ShMOLLI, SASHA, and SAPPHIRE

2. Extracellular volume imaging by magnetic resonance imaging provides insights into overt and sub-clinical myocardial pathology

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