115 citations · 144 across the 9 of their papers we have counts for
10 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…
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…
Diffusion tensor driven image registration: a deep learning approach
Irina Grigorescu, Alena Uus, Daan Christiaens +6
Tracking microsctructural changes in the developing brain relies on accurate inter-subject image registration. However, most methods rely on either structural or diffusion data to…
Perfusion and apparent oxygenation in the human placenta (PERFOX)
Jana Hutter, Anita A. Harteveld, Laurence H. Jackson +9
Purpose: To study placental function - both perfusion and an oxygenation surrogate (T2*)-simultaneously and quantitatively in-vivo. Methods: 15 pregnant women were scanned on a 3T…
In utero diffusion MRI: challenges, advances, and applications
Daan Christiaens, Paddy J. Slator, Lucilio Cordero-Grande +6
In utero diffusion MRI provides unique opportunities to non-invasively study the microstructure of tissue during fetal development. A wide range of developmental processes, such as…