AI RESEARCH
Reinforcing the Weakest Links: Modernizing SIENA with Targeted Deep Learning Integration
arXiv CS.CV
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ArXi:2603.12951v1 Announce Type: cross Percentage Brain Volume Change (PBVC) derived from Magnetic Resonance Imaging (MRI) is a widely used biomarker of brain atrophy, with SIENA among the most established methods for its estimation. However, SIENA relies on classical image processing steps, particularly skull stripping and tissue segmentation, whose failures can propagate through the pipeline and bias atrophy estimates. In this work, we examine whether targeted deep learning substitutions can improve SIENA while preserving its established and interpretable framework.