AtlasSeg: Atlas Prior Guided Dual-UNet for Cortical Segmentation in Fetal Brain MRI

Motivation: Automatic segmentation of fetal brain remains challenging partially due to the dynamically changing anatomical structures during fetal brain development. Goal(s): To enhance segmentation accuracy through incorporating gestational age-specific information as a guidance, we introduce AtlasSeg, a dual-U-shape network with dense attentive interactions. Approach: By providing atlas volume and segmentation label at the corresponding gestational age, AtlasSeg effectively extracts the contextual features of age-specific patterns and structures that assist segmentations. Results: AtlasSeg demonstrated superior performance against six other segmentation networks in both standard and out-of-distribution experiments, in two fetal MRI datasets. Ablation tests further demonstrated the role of atlas guidance. Impact: Through gestational age-specific atlas-guided information, AtlasSeg can serve as an accurate and robust automatic segmentation tool for its superior performance in both in-distribution and out-of-distribution tests, which is useful for quantitative analysis in large-scale fetal brain studies.