activity
20192021
most citedDetecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-specific Atlas Maps

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

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.IV20211 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…

cs.CE2019

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…