Malte Hoffmann, Lilla Zöllei, Adrian V. Dalca
BabySeg is a deep learning framework for accurate infant brain segmentation from diverse MRI protocols, achieving state-of-the-art performance across various age groups and scan types.
Segmenting brain images from MRI scans is crucial for studying brain development, but it's particularly challenging in infants due to motion artifacts and the variability in scanning conditions. The new BabySeg framework uses advanced deep learning techniques to accurately segment infant brain images from a wide variety of MRI scans. This system can handle different types of scans, even those not seen during its training, making it versatile and robust. BabySeg outperforms existing methods in both speed and accuracy, enabling more reliable brain development analysis in young children.
