Dominant Trajectories of Aging‐related Brain Atrophy Identified in 48,949 Individuals via a coupled Cross‐sectional and Longitudinal Non‐negative Matrix Factorization

CCL-NMF offers a robust, interpretable framework for understanding brain aging and neurodegeneration by integrating cross-sectional and longitudinal data. It outperforms cross-sectional approaches, delivering richer representations with superior predictive accuracy, and supports easy application to external datasets through regression-based loadings estimation under a web-accessible server (neuroimagingchart.com).