A Prior Causality‐Guided Multi‐View Diffusion Network for Brain Disorder Classification

Brain disorder classification is a critical task in medical image analysis, requiring accurate diagnosis and classification of various neurological conditions. This paper proposes a Prior Causality-Guided Multi-View Diffusion Network (PCMDN) for brain disorder classification. The network leverages prior causality knowledge to guide the multi-view diffusion process, enabling effective feature learning and classification from multiple perspectives of brain imaging data. The proposed method integrates causality-guided mechanisms with diffusion models to enhance the classification performance for brain disorders.

Journal article

CAAI Transactions on Intelligence Technology