Automated Ventricle Assessment via Three-dimensional Anatomical Reconstruction (AVA-TAR): a computational toolkit for autonomous lateral ventricle assessment in preclinical hydrocephalus models

Key Points

• Automated segmentation improves efficiency in assessing lateral ventricles, benefiting hydrocephalus research.
• The tool demonstrates high accuracy in ventricle morphology quantification from rodent MRI scans.
• Assessment using deep learning algorithms enhances the understanding of hydrocephalus in preclinical models.
• Potential applications may extend from preclinical settings to clinical assessments for hydrocephalus treatment.