141 citations · 404 across the 14 of their papers we have counts for
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QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results
Raghav Mehta, Angelos Filos, Ujjwal Baid +89
Deep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges.…
Synthetic magnetic resonance images for domain adaptation: Application to fetal brain tissue segmentation
Priscille de Dumast, Hamza Kebiri, Kelly Payette +3
The quantitative assessment of the developing human brain in utero is crucial to fully understand neurodevelopment. Thus, automated multi-tissue fetal brain segmentation algorithms…
FaBiAN: A Fetal Brain magnetic resonance Acquisition Numerical phantom
Hélène Lajous, Christopher W. Roy, Tom Hilbert +16
Accurate characterization of in utero human brain maturation is critical as it involves complex and interconnected structural and functional processes that may influence health lat…
The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification
Ujjwal Baid, Satyam Ghodasara, Suyash Mohan +100
The BraTS 2021 challenge celebrates its 10th anniversary and is jointly organized by the Radiological Society of North America (RSNA), the American Society of Neuroradiology (ASNR)…