collaborators

5 papers

eess.IV2026

Towards contrast- and pathology-agnostic clinical fetal brain MRI segmentation using SynthSeg

Ziyao Shang, Misha Kaandorp, Kelly Payette +9

Magnetic resonance imaging (MRI) has played a crucial role in fetal neurodevelopmental research. Structural annotations of MR images are an important step for quantitative analysis…

cs.CV2025

Enhancing efficiency in paediatric brain tumour segmentation using a pathologically diverse single-center clinical dataset

A. Piffer, J. A. Buchner, A. G. Gennari +11

Background Brain tumours are the most common solid malignancies in children, encompassing diverse histological, molecular subtypes and imaging features and outcomes. Paediatric bra…

cs.CV2025

Analysis of the 2024 BraTS Meningioma Radiotherapy Planning Automated Segmentation Challenge

Dominic LaBella, Valeriia Abramova, Mehdi Astaraki +102

The 2024 Brain Tumor Segmentation Meningioma Radiotherapy (BraTS-MEN-RT) challenge aimed to advance automated segmentation algorithms using the largest known multi-institutional da…

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…

eess.IV2025

Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge

Dominic LaBella, Ujjwal Baid, Omaditya Khanna +119

We describe the design and results from the BraTS 2023 Intracranial Meningioma Segmentation Challenge. The BraTS Meningioma Challenge differed from prior BraTS Glioma challenges in…