3 citations · 7 across the 11 of their papers we have counts for
8 papers · 1 filter
Meta-learning Slice-to-Volume Reconstruction in Fetal Brain MRI using Implicit Neural Representations
Maik Dannecker, Thomas Sanchez, Meritxell Bach Cuadra +6
High-resolution slice-to-volume reconstruction (SVR) from multiple motion-corrupted low-resolution 2D slices constitutes a critical step in image-based diagnostics of moving subjec…
The Challenge of Fetal Cardiac MRI Reconstruction Using Deep Learning
Denis Prokopenko, Kerstin Hammernik, Thomas Roberts +3
Dynamic free-breathing fetal cardiac MRI is one of the most challenging modalities, which requires high temporal and spatial resolution to depict rapid changes in a small fetal hea…
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…
Conditional Temporal Attention Networks for Neonatal Cortical Surface Reconstruction
Qiang Ma, Liu Li, Vanessa Kyriakopoulou +4
Cortical surface reconstruction plays a fundamental role in modeling the rapid brain development during the perinatal period. In this work, we propose Conditional Temporal Attentio…
Placenta Segmentation in Ultrasound Imaging: Addressing Sources of Uncertainty and Limited Field-of-View
Veronika A. Zimmer, Alberto Gomez, Emily Skelton +10
Automatic segmentation of the placenta in fetal ultrasound (US) is challenging due to the (i) high diversity of placenta appearance, (ii) the restricted quality in US resulting in…
CAS-Net: Conditional Atlas Generation and Brain Segmentation for Fetal MRI
Liu Li, Qiang Ma, Matthew Sinclair +6
Fetal Magnetic Resonance Imaging (MRI) is used in prenatal diagnosis and to assess early brain development. Accurate segmentation of the different brain tissues is a vital step in…
Fetal MRI by robust deep generative prior reconstruction and diffeomorphic registration: application to gestational age prediction
Lucilio Cordero-Grande, Juan Enrique Ortuño-Fisac, Alena Uus +4
Magnetic resonance imaging of whole fetal body and placenta is limited by different sources of motion affecting the womb. Usual scanning techniques employ single-shot multi-slice s…
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…