This digital poster session explores advanced neuroimaging and computational approaches to understanding healthy brain aging and Alzheimer’s disease across the lifespan. Presentations span molecular and microstructural imaging of amyloid, myelin, iron, and metabolism (e.g., QSM, magnetization transfer, quantitative MRI), alongside AI-driven models for brain age estimation, disease progression prediction, and cognitive decline. Several studies integrate cross-species (human and animal) frameworks and histological validation, highlighting the translational potential of emerging biomarkers. Collectively, the session emphasizes how quantitative imaging and machine learning can improve early detection, biological characterization, and prognostic assessment in aging and Alzheimer’s disease.