63 citations · 98 across the 12 of their papers we have counts for
4 papers · 1 filter
Preserving Marker Specificity with Lightweight Channel-Independent Representation Learning
Simon Gutwein, Arthur Longuefosse, Jun Seita +2
Multiplexed tissue imaging measures dozens of protein markers per cell, yet most deep learning models still apply early channel fusion, assuming shared structure across markers. We…
Conditional Fetal Brain Atlas Learning for Automatic Tissue Segmentation
Johannes Tischer, Patric Kienast, Marlene Stümpflen +3
Magnetic Resonance Imaging (MRI) of the fetal brain has become a key tool for studying brain development in vivo. Yet, its assessment remains challenging due to variability in brai…
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…
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…