Standardized image post-processing of cardiovascular magnetic resonance T1-mapping reduces variability and improves accuracy and consistency in myocardial tissue characterization
<br><strong>Background: </strong>Myocardial T1-mapping is increasingly used in multicentre studies and trials. Inconsistent image analysis introduces variability, hinders differentiation of diseases, and results in larger sample sizes. We present a systematic approach to standardiz...
Main Authors: | Carapella, V, Puchta, H, Lukaschuk, E, Marini, C, Werys, K, Neubauer, S, Ferreira, VM, Piechnik, SK |
---|---|
Format: | Journal article |
Language: | English |
Published: |
Elsevier
2019
|
Similar Items
-
Quality control-driven image segmentation towards reliable automatic image analysis in large-scale cardiovascular magnetic resonance aortic cine imaging
by: Hann, E, et al.
Published: (2019) -
MOCOnet: robust motion correction of cardiovascular magnetic resonance T1 mapping using convolutional neural networks
by: Gonzales, RA, et al.
Published: (2021) -
Myocardial tissue characterization and fibrosis by imaging
by: Karamitsos, TD, et al.
Published: (2019) -
Fast and robust motion correction of cardiovascular magnetic resonance T1-mapping using data-driven convolutional neural networks for generalisability
by: Gonzales, RA, et al.
Published: (2022) -
Development of deep learning virtual native enhancement for gadolinium-free myocardial infarction and viability assessment
by: Zhang, Q, et al.
Published: (2022)