A Modified Fuzzy C-Means Algorithm with Symmetry Information for MR Brain Image Segmentation

Loading...
Thumbnail Image
File version
Author(s)
Jayasuriya, Surani Anuradha
Liew, Alan Wee-Chung
Griffith University Author(s)
Primary Supervisor
Other Supervisors
Editor(s)

IEEE

Date
2013
Size

566393 bytes

File type(s)

application/pdf

Location

Tainan, TAIWAN

License
Abstract

In this paper, we present a novel modified Fuzzy Cmeans algorithm with symmetry information to reduce the effect of noise in brain tissue segmentation in magnetic resonance image (MRI). We integrate brain's bilateral symmetry into the conventional Fuzzy C-means (FCM) as an additional term. In experiments, some synthetic images, and both simulated and real brain images were used to investigate the robustness of the method against noise. Finally, the method was compared with the conventional FCM algorithm. Results show the viability of the approach and the preliminary investigation appears promising.

Journal Title
Conference Title

2013 9TH INTERNATIONAL CONFERENCE ON INFORMATION, COMMUNICATIONS AND SIGNAL PROCESSING (ICICS)

Book Title
Edition
Volume
Issue
Thesis Type
Degree Program
School
Patent number
Funder(s)
Grant identifier(s)
Rights Statement
Rights Statement

© 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Item Access Status
Note
Access the data
Related item(s)
Subject

Computer vision

Persistent link to this record
Citation