3 citations · 7 across the 4 of their papers we have counts for
4 papers
AutOmatic floW planning for fetaL MRI (OWL)
Sara Neves Silva, Tomas Woodgate, Sarah McElroy +11
Two subsequent deep learning networks, one localizing the fetal chest and one identifying a set of landmarks on a coronal whole-uterus balanced steady-state free precession scan, w…
Fully automated planning for anatomical fetal brain MRI on 0.55T
Sara Neves Silva, Sarah McElroy, Jordina Aviles Verdera +11
Purpose: Widening the availability of fetal MRI with fully automatic real-time planning of radiological brain planes on 0.55T MRI. Methods: Deep learning-based detection of key bra…
Multi-task learning for joint weakly-supervised segmentation and aortic arch anomaly classification in fetal cardiac MRI
Paula Ramirez, Alena Uus, Milou P. M. van Poppel +6
Congenital Heart Disease (CHD) is a group of cardiac malformations present already during fetal life, representing the prevailing category of birth defects globally. Our aim in thi…
An automated pipeline for quantitative T2* fetal body MRI and segmentation at low field
Kelly Payette, Alena Uus, Jordina Aviles Verdera +9
Fetal Magnetic Resonance Imaging at low field strengths is emerging as an exciting direction in perinatal health. Clinical low field (0.55T) scanners are beneficial for fetal imagi…