Amyloid Beta

Amyloid-beta (Aβ) plaques are a key pathological hallmark of Alzheimer's disease, and research focuses on accurately detecting and understanding their role in disease progression. Current efforts utilize multimodal MRI data, leveraging deep learning techniques like conditional generative adversarial networks (GANs) and graph convolutional neural networks (GCNs), to predict Aβ burden from readily available MRI scans, thereby potentially reducing reliance on expensive and invasive PET imaging. These advancements aim to improve early diagnosis and personalized treatment strategies for Alzheimer's disease by providing more accessible and accurate assessments of Aβ pathology.