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The findings highlight that deep learning-based longitudinal imaging analysis remains a promising field, though newer temporal architectures and larger datasets may improve success and clinical adoption of these tools.
ASL‐derived IF‐perfusion is reduced in AD and may represent a promising imaging marker of altered CSF‐adjacent water transport physiology and further validation against established biomarkers of CSF dynamics and clearance pathways is warranted.
Training DMG segmentation models with post-treatment scans substantially improves performance in longitudinal clinical trial imaging, enabling more accurate volumetric tracking and response assessment.
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