48 citations · 50 across the 5 of their papers we have counts for
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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…
Automated Quality Control in Image Segmentation: Application to the UK Biobank Cardiac MR Imaging Study
Robert Robinson, Vanya V. Valindria, Wenjia Bai +19
Background: The trend towards large-scale studies including population imaging poses new challenges in terms of quality control (QC). This is a particular issue when automatic proc…
Automatic Assessment of Full Left Ventricular Coverage in Cardiac Cine Magnetic Resonance Imaging with Fisher-Discriminative 3D CNN
Le Zhang, Ali Gooya, Marco Pereanez +5
Cardiac magnetic resonance (CMR) images play a growing role in the diagnostic imaging of cardiovascular diseases. Full coverage of the left ventricle (LV), from base to apex, is a…
Real-time Prediction of Segmentation Quality
Robert Robinson, Ozan Oktay, Wenjia Bai +17
Recent advances in deep learning based image segmentation methods have enabled real-time performance with human-level accuracy. However, occasionally even the best method fails due…
Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image Sequences
Chen Qin, Wenjia Bai, Jo Schlemper +4
Cardiac motion estimation and segmentation play important roles in quantitatively assessing cardiac function and diagnosing cardiovascular diseases. In this paper, we propose a nov…