2 citations · 3 across the 4 of their papers we have counts for
5 papers
STORK: Spatio-Temporal Observation of uterine contRactions via neural networKs
Melissa Schween, Tristan Gottwald, Jordina Aviles Verdera +3
Uterine contractions in fetal MRI are typically identified manually and discarded, limiting insights into contraction dynamics. We formalize Uterine Contractile Activity Detection…
Real-time MRI-based fetal femur length measurement
Johannes Barcsay, Sara Neves Silva, Jordina Aviles Verdera +4
Purpose: To develop and evaluate a real-time method for automatic planning and measurement of fetal femur length - an important indicator of antenatal growth - during MRI. While ro…
PUUMA (Placental patch and whole-Uterus dual-branch U-Mamba-based Architecture): Functional MRI Prediction of Gestational Age at Birth and Preterm Risk
Diego Fajardo-Rojas, Levente Baljer, Jordina Aviles Verdera +6
Preterm birth is a major cause of mortality and lifelong morbidity in childhood. Its complex and multifactorial origins limit the effectiveness of current clinical predictors and i…
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…