271 citations · 535 across the 37 of their papers we have counts for
7 papers · 1 filter
The Impact of Domain Shift on Left and Right Ventricle Segmentation in Short Axis Cardiac MR Images
Devran Ugurlu, Esther Puyol-Anton, Bram Ruijsink +5
Domain shift refers to the difference in the data distribution of two datasets, normally between the training set and the test set for machine learning algorithms. Domain shift is…
Uncertainty-Aware Training for Cardiac Resynchronisation Therapy Response Prediction
Tareen Dawood, Chen Chen, Robin Andlauer +10
Evaluation of predictive deep learning (DL) models beyond conventional performance metrics has become increasingly important for applications in sensitive environments like healthc…
Improved AI-based segmentation of apical and basal slices from clinical cine CMR
Jorge Mariscal-Harana, Naomi Kifle, Reza Razavi +3
Current artificial intelligence (AI) algorithms for short-axis cardiac magnetic resonance (CMR) segmentation achieve human performance for slices situated in the middle of the hear…
Quality-aware Cine Cardiac MRI Reconstruction and Analysis from Undersampled k-space Data
Ines Machado, Esther Puyol-Anton, Kerstin Hammernik +8
Cine cardiac MRI is routinely acquired for the assessment of cardiac health, but the imaging process is slow and typically requires several breath-holds to acquire sufficient k-spa…
A Multimodal Deep Learning Model for Cardiac Resynchronisation Therapy Response Prediction
Esther Puyol-Antón, Baldeep S. Sidhu, Justin Gould +5
We present a novel multimodal deep learning framework for cardiac resynchronisation therapy (CRT) response prediction from 2D echocardiography and cardiac magnetic resonance (CMR)…
A persistent homology-based topological loss for CNN-based multi-class segmentation of CMR
Nick Byrne, James R Clough, Isra Valverde +2
Multi-class segmentation of cardiac magnetic resonance (CMR) images seeks a separation of data into anatomical components with known structure and configuration. The most popular C…
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…