Improving Normative Modeling for Multi-Modal Neuroimaging Data Using Mixture-of-Product-of-Experts Variational Autoencoders

• Published in: Proceedings (International Symposium on Biomedical Imaging) Vol. 2024; pp. 1 - 5
• Main Authors: Kumar, Sayantan, Payne, Philip, Sotiras, Aristeidis
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 01.05.2024
• Subjects: Brain modeling; Data aggregation; Data models; Estimation; mixture-of-product-of-experts; multimodal; Neuroimaging; normative modelling; Pathology; Sociology; variational autoencoders; variational autoencoders; mixture-of-product-of-experts; multimodal; normative modelling

Normative models in neuroimaging learn the brain patterns of healthy population distribution and estimate how disease subjects like Alzheimer's Disease (AD) deviate from the norm. Existing variational autoencoder (VAE)-based normative models using multimodal neuroimaging data aggregate informat...