Abstract
To better use the phase information to compensate the influence of blood flow, the phase unwrapping problem in susceptibility weighted imaging (SWI) is studied in this paper. In order to improve the accuracy of unwrapping, this paper proposes a magnitude image-guided phase unwrapping algorithm of SWI. The basic idea is as follows: (1) reduce the influence of noise by improving the rotational invariant non-local principal component analysis method (PRI-NL-PCA); (2) extract the corresponding solid region in the phase image to avoid the influence of the background noise on the phase unwrapping method; (3) use the phase compensation method to constrain the phase image reconstructed by the K-space. Finally, the reliability of the unwrapping method is evaluated by using four kinds of statistics as quantification index: the number, mean (M), variance (Var), and positive percentage (Pos) and negative percentage (Neg) of phasic error points. By comparing the simulated data with 226 sets of true head SWI data, the results show that the proposed algorithm has high accuracy compared with the classical branch cut method and the least squares method.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
