Brain Diffuser: An End-to-End Brain Image to Brain Network Pipeline
This addresses the need for more efficient and objective brain network analysis tools in diagnosing Alzheimer's disease, though it appears incremental as it builds on existing diffusion-based methods.
The paper tackles the problem of generating structural brain networks from diffusion tensor images for Alzheimer's disease analysis, proposing Brain Diffuser, which outperforms existing toolkits on the ADNI database.
Brain network analysis is essential for diagnosing and intervention for Alzheimer's disease (AD). However, previous research relied primarily on specific time-consuming and subjective toolkits. Only few tools can obtain the structural brain networks from brain diffusion tensor images (DTI). In this paper, we propose a diffusion based end-to-end brain network generative model Brain Diffuser that directly shapes the structural brain networks from DTI. Compared to existing toolkits, Brain Diffuser exploits more structural connectivity features and disease-related information by analyzing disparities in structural brain networks across subjects. For the case of Alzheimer's disease, the proposed model performs better than the results from existing toolkits on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.