Light-weight neural network for intra-voxel structure analysis.

ABSTRACT: We present a novel neural network-based method for analyzing intra-voxel structures, addressing critical challenges in diffusion-weighted MRI analysis for brain connectivity and development studies. The network architecture, called the Local Neighborhood Neural Network, is designed to use the spatial correlations of neighboring voxels for an enhanced inference while reducing parameter overhead. Our model exploits these relationships to improve the analysis of complex structures and noisy data environments. We adopt a self-supervised approach to address the lack of ground truth data, generating signals of voxel neighborhoods to integrate the training set. This eliminates the need for manual annotations and facilitates training under realistic conditions. Comparative analyses show that our m

SUBMITTER: Aguayo-Gonzalez JF 

PROVIDER: S-EPMC11417038 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature