Main Paths of Brain Fibers in Diffusion Images Mixed with a Noise to Improve Performance of Tractography Algorithm-Evaluation in Phantom

Abstract

Background: Some voxels may alter the tractography results due to unintentional alteration of noises and other unwanted factors.Objective: This study aimed to investigate the effect of local phase features on tractography results providing data are mixed by a Gaussian or random distribution noise.Material and Methods: In this simulation study, a mask was firstly designed based on the local phase features to decrease false-negative and -positive tractography results. The local phase features are calculated according to the local structures of images, which can be zero-dimensional, meaning just one point (equivalent to noise in tractography algorithm), a line (equivalent to a simple fiber), or an edge (equivalent to structures more complex than a simple fiber). A digital phantom evaluated the feasibility current model with the maximum complexities of configurations in fibers, including crossing fibers. In this paper, the diffusion images were mixed separately by a Gaussian or random distribution noise in 2 forms: a zero-mean noise and a noise with a mean of data.Results: The local mask eliminates the pixels of unfitted values with the main structures of images, due to noise or other interferer factors. Conclusion: The local phase features of diffusion images are an innovative solution to determine principal diffusion directions.

Keywords

• diffusion tractography
• diffusion magnetic resonance imaging
• features
• gaussian distribution
• local phase
• noise
• feasibility studies
• brain