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Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers: 14th International Workshop, STACOM 2023, Held in Conjunction With MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Revised Selected Papers

2024

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Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers: 13th International Workshop, STACOM 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Revised Selected Papers

1, 2023

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Aortic Distensibility Measured by Automated Analysis of Magnetic Resonance Imaging Predicts Adverse Cardiovascular Events in UK Biobank

Journal of the American Heart Association, 2022-12, Vol.11 (23), p.e026361-e026361

2022

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Fully Automated, Quality-Controlled Cardiac Analysis From CMR: Validation and Large-Scale Application to Characterize Cardiac Function

JACC. Cardiovascular imaging, 2020-03, Vol.13 (3), p.684-695

2020

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Deep Learning for Classification and Selection of Cine CMR Images to Achieve Fully Automated Quality-Controlled CMR Analysis From Scanner to Report

Frontiers in cardiovascular medicine, 2021-10, Vol.8, p.742640-742640

2021

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Digital Bank Runs: A Deep Neural Network Approach

Sustainability, 2021-02, Vol.13 (3), p.1513

2021

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Hemodynamic Determinants of Elevated Blood Pressure and Hypertension in the Middle to Older-Age UK Population: A UK Biobank Imaging Study

Hypertension (Dallas, Tex. 1979), 2023-11, Vol.80 (11), p.2473-2484

2023

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Global and Local Interpretability for Cardiac MRI Classification

Medical Image Computing and Computer Assisted Intervention – MICCAI 2019, p.656-664

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Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging: 12th International Workshop, CLIP 2023 1st International Workshop, FAIMI 2023 and 2nd International Workshop, EPIMI 2023 Vancouver, BC, Canada, October 8 and October 12, 2023 Proceedings

1st ed. 2023., 2023

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Deep learning-based quality-controlled spleen assessment from ultrasound images

Biomedical signal processing and control, 2022-07, Vol.76, p.103724, Article 103724

2022

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Addressing Deep Learning Model Calibration Using Evidential Neural Networks and Uncertainty-Aware Training

2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), 2023, Vol.34, p.1-5

2023

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Fairness in Cardiac MR Image Analysis: An Investigation of Bias Due to Data Imbalance in Deep Learning Based Segmentation

Medical Image Computing and Computer Assisted Intervention – MICCAI 2021, p.413-423

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Fully Automated, Quality-Controlled Cardiac Analysis From CMR

JACC. Cardiovascular imaging, 2020-03, Vol.13 (3), p.684-695

2020

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Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge: 12th International Workshop, STACOM 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Revised Selected Papers

1, 2022

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Deep Learning-Based Segmentation of Pleural Effusion from Ultrasound Using Coordinate Convolutions

Distributed, Collaborative, and Federated Learning, and Affordable AI and Healthcare for Resource Diverse Global Health, p.168-177

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Fully Automated Segmentation-Based Respiratory Motion Correction of Multiplanar Cardiac Magnetic Resonance Images for Large-Scale Datasets

Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017, p.332-340

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Assessing the Impact of Blood Pressure on Cardiac Function Using Interpretable Biomarkers and Variational Autoencoders

Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges, p.22-30

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Automated quantification of myocardial tissue characteristics from native T1 mapping using neural networks with uncertainty-based quality-control

Journal of cardiovascular magnetic resonance, 2020-08, Vol.22 (1), p.60-60, Article 60

2020

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Automatic Detection of Extra-Cardiac Findings in Cardiovascular Magnetic Resonance

Medical Image Understanding and Analysis, p.98-107

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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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Synthesising Images and Labels Between MR Sequence Types with CycleGAN

Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data, p.45-53

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Deep Learning Using K-Space Based Data Augmentation for Automated Cardiac MR Motion Artefact Detection

Medical Image Computing and Computer Assisted Intervention – MICCAI 2018, p.250-258

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Deep Learning for Automatic Spleen Length Measurement in Sickle Cell Disease Patients

Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis, p.33-41

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A Systematic Study of Race and Sex Bias in CNN-Based Cardiac MR Segmentation

Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers, p.233-244

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An Investigation into the Impact of Deep Learning Model Choice on Sex and Race Bias in Cardiac MR Segmentation

Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging, p.215-224

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Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers: 14th International Workshop, STACOM 2023, Held in Conjunction With MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Revised Selected Papers

Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers: 13th International Workshop, STACOM 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Revised Selected Papers

Aortic Distensibility Measured by Automated Analysis of Magnetic Resonance Imaging Predicts Adverse Cardiovascular Events in UK Biobank

Fully Automated, Quality-Controlled Cardiac Analysis From CMR: Validation and Large-Scale Application to Characterize Cardiac Function

Deep Learning for Classification and Selection of Cine CMR Images to Achieve Fully Automated Quality-Controlled CMR Analysis From Scanner to Report

Digital Bank Runs: A Deep Neural Network Approach

Hemodynamic Determinants of Elevated Blood Pressure and Hypertension in the Middle to Older-Age UK Population: A UK Biobank Imaging Study

Global and Local Interpretability for Cardiac MRI Classification

Deep learning-based quality-controlled spleen assessment from ultrasound images

Addressing Deep Learning Model Calibration Using Evidential Neural Networks and Uncertainty-Aware Training

Fairness in Cardiac MR Image Analysis: An Investigation of Bias Due to Data Imbalance in Deep Learning Based Segmentation

Fully Automated, Quality-Controlled Cardiac Analysis From CMR

Deep Learning-Based Segmentation of Pleural Effusion from Ultrasound Using Coordinate Convolutions

Fully Automated Segmentation-Based Respiratory Motion Correction of Multiplanar Cardiac Magnetic Resonance Images for Large-Scale Datasets

Assessing the Impact of Blood Pressure on Cardiac Function Using Interpretable Biomarkers and Variational Autoencoders

Automated quantification of myocardial tissue characteristics from native T1 mapping using neural networks with uncertainty-based quality-control

Automatic Detection of Extra-Cardiac Findings in Cardiovascular Magnetic Resonance

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

Synthesising Images and Labels Between MR Sequence Types with CycleGAN

Deep Learning Using K-Space Based Data Augmentation for Automated Cardiac MR Motion Artefact Detection

Deep Learning for Automatic Spleen Length Measurement in Sickle Cell Disease Patients

A Systematic Study of Race and Sex Bias in CNN-Based Cardiac MR Segmentation

An Investigation into the Impact of Deep Learning Model Choice on Sex and Race Bias in Cardiac MR Segmentation

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