activity
20192023
most citedAutomated quantification of myocardial tissue characteristics from native T1 mapping using neural networks with Bayesian inference for uncertainty-based quality-control

48 citations · 81 across the 10 of their papers we have counts for

collaborators

11 papers

cs.LG2023

Automatic retrieval of corresponding US views in longitudinal examinations

Hamideh Kerdegari, Tran Huy Nhat Phung1, Van Hao Nguyen +12

Skeletal muscle atrophy is a common occurrence in critically ill patients in the intensive care unit (ICU) who spend long periods in bed. Muscle mass must be recovered through phys…

eess.IV2023

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…

eess.IV2022

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…

eess.IV2022

An AI tool for automated analysis of large-scale unstructured clinical cine CMR databases

Jorge Mariscal-Harana, Clint Asher, Vittoria Vergani +9

Artificial intelligence (AI) techniques have been proposed for automating analysis of short axis (SAX) cine cardiac magnetic resonance (CMR), but no CMR analysis tool exists to aut…

eess.IV2021

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…

eess.IV2021★ 1 cited

Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-specific Atlas Maps

Samuel Budd, Matthew Sinclair, Thomas Day +11

Fetal ultrasound screening during pregnancy plays a vital role in the early detection of fetal malformations which have potential long-term health impacts. The level of skill requi…

cs.CV2021

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…

eess.IV2020

Quality-aware semi-supervised learning for CMR segmentation

Bram Ruijsink, Esther Puyol-Anton, Ye Li +4

One of the challenges in developing deep learning algorithms for medical image segmentation is the scarcity of annotated training data. To overcome this limitation, data augmentati…

eess.IV2020★ 48 cited

Automated quantification of myocardial tissue characteristics from native T1 mapping using neural networks with Bayesian inference for uncertainty-based quality-control

Esther Puyol Anton, Bram Ruijsink, Christian F. Baumgartner +4

Tissue characterisation with CMR parametric mapping has the potential to detect and quantify both focal and diffuse alterations in myocardial structure not assessable by late gadol…

cs.LG2019★ 5 cited

Assessing the Impact of Blood Pressure on Cardiac Function Using Interpretable Biomarkers and Variational Autoencoders

Esther Puyol-Antón, Bram Ruijsink, James R. Clough +4

Maintaining good cardiac function for as long as possible is a major concern for healthcare systems worldwide and there is much interest in learning more about the impact of differ…

cs.CE2019★ 27 cited

A partition of unity approach to fluid mechanics and fluid-structure interaction

Maximilian Balmus, Andre Massing, Johan Hoffman +2

For problems involving large deformations of thin structures, simulating fluid-structure interaction (FSI) remains challenging largely due to the need to balance computational feas…