A modality-agnostic deep learning model reconstructs healthy brain anatomy from pathological CT and MRI scans, trained with fluid-dynamics-based synthetic anomaly generation and contralateral brain symmetry.
Robust machine learning segmentation for large-scale analysis of heterogeneous clinical brain MRI datasets
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Unraveling Normal Anatomy via Fluid-Driven Anomaly Randomization
A modality-agnostic deep learning model reconstructs healthy brain anatomy from pathological CT and MRI scans, trained with fluid-dynamics-based synthetic anomaly generation and contralateral brain symmetry.