Esther Puyol-Antón

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King's College London

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

The subject of "fairness" in artificial intelligence (AI) refers to asse...
06/23/2021 ∙ by Esther Puyol-Antón, et al. ∙ 39 ∙ share

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Probabilistic 3D surface reconstruction from sparse MRI information

Surface reconstruction from magnetic resonance (MR) imaging data is indi...
10/05/2020 ∙ by Katarína Tóthová, et al. ∙ 10 ∙ share

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

Sickle Cell Disease (SCD) is one of the most common genetic diseases in ...
09/06/2020 ∙ by Zhen Yuan, et al. ∙ 37 ∙ share

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Quality-aware semi-supervised learning for CMR segmentation

One of the challenges in developing deep learning algorithms for medical...
09/01/2020 ∙ by Bram Ruijsink, et al. ∙ 11 ∙ share

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

Tissue characterisation with CMR parametric mapping has the potential to...
01/31/2020 ∙ by Esther Puyol-Antón, et al. ∙ 9 ∙ share

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Deep Learning Based Detection and Correction of Cardiac MR Motion Artefacts During Reconstruction for High-Quality Segmentation

Segmenting anatomical structures in medical images has been successfully...
10/11/2019 ∙ by Ilkay Oksuz, et al. ∙ 34 ∙ share

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Deep Learning Based Detection and Correction of Cardiac MR Motion Artefacts During Reconstruction for High-Quality Segmentatio

Segmenting anatomical structures in medical images has been successfully...
10/11/2019 ∙ by Ilkay Oksuz, et al. ∙ 27 ∙ share

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

Maintaining good cardiac function for as long as possible is a major con...
08/13/2019 ∙ by Esther Puyol-Antón, et al. ∙ 3 ∙ share

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Global and Local Interpretability for Cardiac MRI Classification

Deep learning methods for classifying medical images have demonstrated i...
06/14/2019 ∙ by James R. Clough, et al. ∙ 4 ∙ share

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Detection and Correction of Cardiac MR Motion Artefacts during Reconstruction from K-space

In fully sampled cardiac MR (CMR) acquisitions, motion can lead to corru...
06/12/2019 ∙ by lkay Oksuz, et al. ∙ 3 ∙ share

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Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning

Good quality of medical images is a prerequisite for the success of subs...
10/29/2018 ∙ by lkay Oksuz, et al. ∙ 2 ∙ share

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Deep Learning using K-space Based Data Augmentation for Automated Cardiac MR Motion Artefact Detection

Quality assessment of medical images is essential for complete automatio...
08/15/2018 ∙ by Ilkay Oksuz, et al. ∙ 2 ∙ share

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Uncertainty Quantification in CNN-Based Surface Prediction Using Shape Priors

Surface reconstruction is a vital tool in a wide range of areas of medic...
07/30/2018 ∙ by Katarína Tóthová, et al. ∙ 6 ∙ share

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Learning associations between clinical information and motion-based descriptors using a large scale MR-derived cardiac motion atlas

The availability of large scale databases containing imaging and non-ima...
07/27/2018 ∙ by Esther Puyol-Antón, et al. ∙ 0 ∙ share

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