48 citations · 95 across the 21 of their papers we have counts for
24 papers
Invisible Attributes, Visible Biases: Exploring Demographic Shortcuts in MRI-based Alzheimer's Disease Classification
Akshit Achara, Esther Puyol Anton, Alexander Hammers +1
Magnetic resonance imaging (MRI) is the gold standard for brain imaging. Deep learning (DL) algorithms have been proposed to aid in the diagnosis of diseases such as Alzheimer's di…
An investigation into the causes of race bias in AI-based cine CMR segmentation
Tiarna Lee, Esther Puyol-Anton, Bram Ruijsink +5
Artificial intelligence (AI) methods are being used increasingly for the automated segmentation of cine cardiac magnetic resonance (CMR) imaging. However, these methods have been s…
Uncertainty Aware Training to Improve Deep Learning Model Calibration for Classification of Cardiac MR Images
Tareen Dawood, Chen Chen, Baldeep S. Sidhua +9
Quantifying uncertainty of predictions has been identified as one way to develop more trustworthy artificial intelligence (AI) models beyond conventional reporting of performance m…
Deep Learning Framework for Spleen Volume Estimation from 2D Cross-sectional Views
Zhen Yuan, Esther Puyol-Anton, Haran Jogeesvaran +2
Abnormal spleen enlargement (splenomegaly) is regarded as a clinical indicator for a range of conditions, including liver disease, cancer and blood diseases. While spleen length me…
Addressing Deep Learning Model Calibration Using Evidential Neural Networks and Uncertainty-Aware Training
Tareen Dawood, Emily Chan, Reza Razavi +2
In terms of accuracy, deep learning (DL) models have had considerable success in classification problems for medical imaging applications. However, it is well-known that the output…
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…