35 citations · 38 across the 14 of their papers we have counts for
6 papers · 1 filter
Comparison of Loss Functions for Robust Deep Learning-based Echocardiography Segmentation when Learning with Partially Labelled Data from Multiple Domains
Iman Islam, Esther Puyol-Antón, Bram Ruijsink +2
Echocardiography is the first imaging modality used for assessing cardiac function, and accurate segmentation of cardiac structures is essential for deriving biomarkers. However, t…
Detecting and refurbishing ground truth errors during training of deep learning-based echocardiography segmentation models
Iman Islam, Bram Ruijsink, Andrew J. Reader +1
Deep learning-based medical image segmentation typically relies on ground truth (GT) labels obtained through manual annotation, but these can be prone to random errors or systemati…
Label Dropout: Improved Deep Learning Echocardiography Segmentation Using Multiple Datasets With Domain Shift and Partial Labelling
Iman Islam, Esther Puyol-Antón, Bram Ruijsink +2
Echocardiography (echo) is the first imaging modality used when assessing cardiac function. The measurement of functional biomarkers from echo relies upon the segmentation of cardi…
Fairness in Cardiac MR Image Analysis: An Investigation of Bias Due to Data Imbalance in Deep Learning Based Segmentation
Esther Puyol-Anton, Bram Ruijsink, Stefan K. Piechnik +4
The subject of "fairness" in artificial intelligence (AI) refers to assessing AI algorithms for potential bias based on demographic characteristics such as race and gender, and the…
Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning
Ilkay Oksuz, Bram Ruijsink, Esther Puyol-Anton +8
Good quality of medical images is a prerequisite for the success of subsequent image analysis pipelines. Quality assessment of medical images is therefore an essential activity and…
Deep Learning using K-space Based Data Augmentation for Automated Cardiac MR Motion Artefact Detection
Ilkay Oksuz, Bram Ruijsink, Esther Puyol-Anton +6
Quality assessment of medical images is essential for complete automation of image processing pipelines. For large population studies such as the UK Biobank, artefacts such as thos…