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

Authors :
Alireza Shirazinodeh
Hadis Faraji
Sam Sharifzadeh Javidi
Amir Homayoun Jafari
Mohammadreza Nazemzadeh
Hamidreza Saligheh Rad
Source :
Journal of Biomedical Physics and Engineering, Vol 14, Iss 4, Pp 357-364 (2024)
Publication Year :
2024
Publisher :
Shiraz University of Medical Sciences, 2024.

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.

Details

Language :
English
ISSN :
22517200 and 21081387
Volume :
14
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Journal of Biomedical Physics and Engineering
Publication Type :
Academic Journal
Accession number :
edsdoj.4543a6b472bf4e27a4c0eeb9eb77b4ea
Document Type :
article
Full Text :
https://doi.org/10.31661/jbpe.v0i0.2108-1387