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Methods and Results

To train our deep learning model, lateral ventricles were manually annotated in 103 scans. We split these scans randomly with a ratio of 4: 1 for training and validation respectively. We trained a U-Net to segment lateral ventricles in each slice. Another U-Net model was trained to segment cranial vault using a similar process. Models were validated using DICE score metric versus the annotations.