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Myocardial T1 mapping and extracellular volume quantification: a Society for Cardiovascular Magnetic Resonance (SCMR) and CMR Working Group of the European Society of Cardiology consensus statement

Journal of cardiovascular magnetic resonance, 2013-10, Vol.15 (1), p.92-92, Article 92

2013

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Estimating Uncertainty in Neural Networks for Cardiac MRI Segmentation: A Benchmark Study

IEEE transactions on biomedical engineering, 2023-06, Vol.70 (6), p.1955-1966

2023

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CMR Parametric Mapping as a Tool for Myocardial Tissue Characterization

Korean Circulation Journal, 2020, 50(8), , pp.658-676

2020

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Automated quality control in image segmentation: application to the UK Biobank cardiovascular magnetic resonance imaging study

Journal of cardiovascular magnetic resonance, 2019-03, Vol.21 (1), p.18-18, Article 18

2019

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Standardization of T1-mapping in cardiovascular magnetic resonance using clustered structuring for benchmarking normal ranges

International journal of cardiology, 2021-03, Vol.326, p.220-225

2021

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Cardiac stress T1-mapping response and extracellular volume stability of MOLLI-based T1-mapping methods

Scientific reports, 2021-06, Vol.11 (1), p.13568-13568, Article 13568

2021

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Improving the Generalizability of Convolutional Neural Network-Based Segmentation on CMR Images

Frontiers in cardiovascular medicine, 2020-06, Vol.7, p.105-105

2020

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Automated localization and quality control of the aorta in cine CMR can significantly accelerate processing of the UK Biobank population data

PloS one, 2019-02, Vol.14 (2), p.e0212272-e0212272

2019

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Fairness in Cardiac Magnetic Resonance Imaging: Assessing Sex and Racial Bias in Deep Learning-Based Segmentation

Frontiers in cardiovascular medicine, 2022-04, Vol.9, p.859310

2022

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Improving robustness of automatic cardiac function quantification from cine magnetic resonance imaging using synthetic image data

Scientific reports, 2022-02, Vol.12 (1), p.2391-2391, Article 2391

2022

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Editorial Expression of Concern: Splenic T1-mapping: a novel quantitative method for assessing adenosine stress adequacy for cardiovascular magnetic resonance

Journal of cardiovascular magnetic resonance, 2023-05, Vol.25 (1), p.27-27, Article 27

2023

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Radiomics Signatures of Cardiovascular Risk Factors in Cardiac MRI: Results From the UK Biobank

Frontiers in cardiovascular medicine, 2020-11, Vol.7, p.591368

2020

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Diagnostic Value of Pre-Contrast T1 Mapping in Acute and Chronic Myocardial Infarction

JACC. Cardiovascular imaging, 2013-06, Vol.6 (6), p.739-742

2013

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T1 measurements in the human myocardium: The effects of magnetization transfer on the SASHA and MOLLI sequences

Magnetic resonance in medicine, 2013-09, Vol.70 (3), p.664-670

2013

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Improving cardiac MRI convolutional neural network segmentation on small training datasets and dataset shift: A continuous kernel cut approach

Medical image analysis, 2020-04, Vol.61, p.101636-101636, Article 101636

2020

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MOCOnet: Robust Motion Correction of Cardiovascular Magnetic Resonance T1 Mapping Using Convolutional Neural Networks

Frontiers in cardiovascular medicine, 2021-11, Vol.8, p.768245-768245

2021

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Deep neural network ensemble for on-the-fly quality control-driven segmentation of cardiac MRI T1 mapping

Medical image analysis, 2021-07, Vol.71, p.102029-102029, Article 102029

2021

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Acute changes in myocardial tissue characteristics during hospitalization in patients with COVID-19

Frontiers in cardiovascular medicine, 2023-02, Vol.10, p.1097974-1097974

2023

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Quality control-driven deep ensemble for accountable automated segmentation of cardiac magnetic resonance LGE and VNE images

Frontiers in cardiovascular medicine, 2023-09, Vol.10, p.1213290-1213290

2023

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Toward Replacing Late Gadolinium Enhancement With Artificial Intelligence Virtual Native Enhancement for Gadolinium-Free Cardiovascular Magnetic Resonance Tissue Characterization in Hypertrophic Cardiomyopathy

Circulation (New York, N.Y.), 2021-08, Vol.144 (8), p.589-599

2021

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Myocardial T1 mapping and extracellular volume quantification: an overview of technical and biological confounders

The International Journal of Cardiovascular Imaging, 2018-01, Vol.34 (1), p.3-14

2018

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Mitral Annular Disjunction Assessed Using CMR Imaging: Insights From the UK Biobank Population Study

JACC. Cardiovascular imaging, 2022-11, Vol.15 (11), p.1856-1866

2022

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State-of-the-art review: stress T1 mapping—technical considerations, pitfalls and emerging clinical applications

Magma (New York, N.Y.), 2018-02, Vol.31 (1), p.131-141

2018

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Associations of Meat and Fish Consumption With Conventional and Radiomics Cardiovascular Magnetic Resonance Phenotypes in the UK Biobank

Frontiers in cardiovascular medicine, 2021-05, Vol.8, p.667849-667849

2021

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Correction to: Adenosine stress CMR T1-mapping detects early microvascular dysfunction in patients with type 2 diabetes mellitus without obstructive coronary artery disease

Journal of cardiovascular magnetic resonance, 2017-12, Vol.19 (1), p.99-99, Article 99

2017

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Myocardial T1 mapping and extracellular volume quantification: a Society for Cardiovascular Magnetic Resonance (SCMR) and CMR Working Group of the European Society of Cardiology consensus statement

Estimating Uncertainty in Neural Networks for Cardiac MRI Segmentation: A Benchmark Study

CMR Parametric Mapping as a Tool for Myocardial Tissue Characterization

Automated quality control in image segmentation: application to the UK Biobank cardiovascular magnetic resonance imaging study

Standardization of T1-mapping in cardiovascular magnetic resonance using clustered structuring for benchmarking normal ranges

Cardiac stress T1-mapping response and extracellular volume stability of MOLLI-based T1-mapping methods

Improving the Generalizability of Convolutional Neural Network-Based Segmentation on CMR Images

Automated localization and quality control of the aorta in cine CMR can significantly accelerate processing of the UK Biobank population data

Fairness in Cardiac Magnetic Resonance Imaging: Assessing Sex and Racial Bias in Deep Learning-Based Segmentation

Improving robustness of automatic cardiac function quantification from cine magnetic resonance imaging using synthetic image data

Editorial Expression of Concern: Splenic T1-mapping: a novel quantitative method for assessing adenosine stress adequacy for cardiovascular magnetic resonance

Radiomics Signatures of Cardiovascular Risk Factors in Cardiac MRI: Results From the UK Biobank

Diagnostic Value of Pre-Contrast T1 Mapping in Acute and Chronic Myocardial Infarction

T1 measurements in the human myocardium: The effects of magnetization transfer on the SASHA and MOLLI sequences

Improving cardiac MRI convolutional neural network segmentation on small training datasets and dataset shift: A continuous kernel cut approach

MOCOnet: Robust Motion Correction of Cardiovascular Magnetic Resonance T1 Mapping Using Convolutional Neural Networks

Deep neural network ensemble for on-the-fly quality control-driven segmentation of cardiac MRI T1 mapping

Acute changes in myocardial tissue characteristics during hospitalization in patients with COVID-19

Quality control-driven deep ensemble for accountable automated segmentation of cardiac magnetic resonance LGE and VNE images

Toward Replacing Late Gadolinium Enhancement With Artificial Intelligence Virtual Native Enhancement for Gadolinium-Free Cardiovascular Magnetic Resonance Tissue Characterization in Hypertrophic Cardiomyopathy

Myocardial T1 mapping and extracellular volume quantification: an overview of technical and biological confounders

Mitral Annular Disjunction Assessed Using CMR Imaging: Insights From the UK Biobank Population Study

State-of-the-art review: stress T1 mapping—technical considerations, pitfalls and emerging clinical applications

Associations of Meat and Fish Consumption With Conventional and Radiomics Cardiovascular Magnetic Resonance Phenotypes in the UK Biobank

Correction to: Adenosine stress CMR T1-mapping detects early microvascular dysfunction in patients with type 2 diabetes mellitus without obstructive coronary artery disease

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