271 citations · 535 across the 37 of their papers we have counts for
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Automated Quality Controlled Analysis of 2D Phase Contrast Cardiovascular Magnetic Resonance Imaging
Emily Chan, Ciaran O'Hanlon, Carlota Asegurado Marquez +11
Flow analysis carried out using phase contrast cardiac magnetic resonance imaging (PC-CMR) enables the quantification of important parameters that are used in the assessment of car…
A systematic study of race and sex bias in CNN-based cardiac MR segmentation
Tiarna Lee, Esther Puyol-Anton, Bram Ruijsink +2
In computer vision there has been significant research interest in assessing potential demographic bias in deep learning models. One of the main causes of such bias is imbalance in…
A Study of Demographic Bias in CNN-based Brain MR Segmentation
Stefanos Ioannou, Hana Chockler, Alexander Hammers +1
Convolutional neural networks (CNNs) are increasingly being used to automate the segmentation of brain structures in magnetic resonance (MR) images for research studies. In other a…
Deep Learning-based Segmentation of Pleural Effusion From Ultrasound Using Coordinate Convolutions
Germain Morilhat, Naomi Kifle, Sandra FinesilverSmith +7
In many low-to-middle income (LMIC) countries, ultrasound is used for assessment of pleural effusion. Typically, the extent of the effusion is manually measured by a sonographer, l…
A Deep Learning-based Integrated Framework for Quality-aware Undersampled Cine Cardiac MRI Reconstruction and Analysis
Inês P. Machado, Esther Puyol-Antón, Kerstin Hammernik +10
Cine cardiac magnetic resonance (CMR) imaging is considered the gold standard for cardiac function evaluation. However, cine CMR acquisition is inherently slow and in recent decade…
AI-enabled Assessment of Cardiac Systolic and Diastolic Function from Echocardiography
Esther Puyol-Antón, Bram Ruijsink, Baldeep S. Sidhu +12
Left ventricular (LV) function is an important factor in terms of patient management, outcome, and long-term survival of patients with heart disease. The most recently published cl…