Document Type : Original Research

Authors

1 PhD Candidate, Department of Medical Physics and Biomedical Engineering, Medicine School, Tehran University of Medical Sciences, Tehran, Iran

2 MSc, Research Center for Molecular and Cellular Imaging Advanced Medical Technologies and Equipment, Tehran University of Medical Sciences

3 PhD, Research Center for Biomedical Technologies and Robotics (RCBTR) Tehran University of Medical Sciences, Tehran, Iran

4 PhD, Department of Medical Physics and Biomedical Engineering, Medicine School, Tehran University of Medical Sciences, Tehran, Iran

5 PhD, Research Center for Molecular and Cellular Imaging Advanced Medical Technologies and Equipment, Tehran University of Medical Sciences, Tehran, Iran

6 PhD, Quantitative Medical Imaging Systems Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran

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