23 citations · 58 across the 5 of their papers we have counts for
5 papers
Automatic quality control in multi-centric fetal brain MRI super-resolution reconstruction
Thomas Sanchez, Vladyslav Zalevskyi, Angeline Mihailov +7
Quality control (QC) has long been considered essential to guarantee the reliability of neuroimaging studies. It is particularly important for fetal brain MRI, where acquisitions a…
Pathological MRI Segmentation by Synthetic Pathological Data Generation in Fetuses and Neonates
Misha P. T Kaandorp, Damola Agbelese, Hosna Asma-ull +6
Developing new methods for the automated analysis of clinical fetal and neonatal MRI data is limited by the scarcity of annotated pathological datasets and privacy concerns that of…
Multi-Center Fetal Brain Tissue Annotation (FeTA) Challenge 2022 Results
Kelly Payette, Céline Steger, Roxane Licandro +64
Segmentation is a critical step in analyzing the developing human fetal brain. There have been vast improvements in automatic segmentation methods in the past several years, and th…
FetMRQC: a robust quality control system for multi-centric fetal brain MRI
Thomas Sanchez, Oscar Esteban, Yvan Gomez +8
Fetal brain MRI is becoming an increasingly relevant complement to neurosonography for perinatal diagnosis, allowing fundamental insights into fetal brain development throughout ge…
The Federated Tumor Segmentation (FeTS) Challenge
Sarthak Pati, Ujjwal Baid, Maximilian Zenk +29
This manuscript describes the first challenge on Federated Learning, namely the Federated Tumor Segmentation (FeTS) challenge 2021. International challenges have become the standar…