7 citations · 12 across the 8 of their papers we have counts for
8 papers
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…
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,…
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…
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…
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…
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…
SYNCS: Synthetic Data and Contrastive Self-Supervised Training for Central Sulcus Segmentation
Vladyslav Zalevskyi, Kristoffer Hougaard Madsen
Bipolar disorder (BD) and schizophrenia (SZ) are severe mental disorders with profound societal impact. Identifying risk markers early is crucial for understanding disease progress…
Improving cross-domain brain tissue segmentation in fetal MRI with synthetic data
Vladyslav Zalevskyi, Thomas Sanchez, Margaux Roulet +4
Segmentation of fetal brain tissue from magnetic resonance imaging (MRI) plays a crucial role in the study of in utero neurodevelopment. However, automated tools face substantial d…