most citedEvaluating Synthetic Data Generation for Domain Generalization in Fetal Brain MRI Segmentation

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6 papers

eess.IV20261 cited

Evaluating Synthetic Data Generation for Domain Generalization in Fetal Brain MRI Segmentation

Vladyslav Zalevskyi, Thomas Sanchez, Margaux Roulet +10

Fetal brain tissue segmentation from magnetic resonance imaging (MRI) is crucial for studying neurodevelopment, but remains challenging due to data heterogeneity and limited annota…

physics.app-ph2025

T2 mapping at 0.55 T using Ultra-Fast Spin Echo MRI

Margaux Roulet, Hamza Kebiri, Busra Bulut +9

Low-field T2 mapping MRI can democratize neuropediatric imaging by improving accessibility and providing quantitative biomarkers of brain development. \textbf{Purpose:} To evaluate…

eess.IV2025

Segmenting infant brains across magnetic fields: Domain randomization and annotation curation in ultra-low field MRI

Vladyslav Zalevskyi, Dondu-Busra Bulut, Thomas Sanchez +1

Early identification of neurodevelopmental disorders relies on accurate segmentation of brain structures in infancy, a task complicated by rapid brain growth, poor tissue contrast,…

cs.CV2025

Enhancing Corpus Callosum Segmentation in Fetal MRI via Pathology-Informed Domain Randomization

Marina Grifell i Plana, Vladyslav Zalevskyi, Léa Schmidt +6

Accurate fetal brain segmentation is crucial for extracting biomarkers and assessing neurodevelopment, especially in conditions such as corpus callosum dysgenesis (CCD), which can…

cs.CV2025

Physics-Informed Joint Multi-TE Super-Resolution with Implicit Neural Representation for Robust Fetal T2 Mapping

Busra Bulut, Maik Dannecker, Thomas Sanchez +9

T2 mapping in fetal brain MRI has the potential to improve characterization of the developing brain, especially at mid-field (0.55T), where T2 decay is slower. However, this is cha…

cs.CV2025

Advances in Automated Fetal Brain MRI Segmentation and Biometry: Insights from the FeTA 2024 Challenge

Vladyslav Zalevskyi, Thomas Sanchez, Misha Kaandorp +67

Accurate fetal brain tissue segmentation and biometric analysis are essential for studying brain development in utero. The FeTA Challenge 2024 advanced automated fetal brain MRI an…