By Topic

Gauss-Hermite moments application in medical image segmentation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $33
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Xia Zheng ; State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, 100875, China ; Mo Dai ; Mingquan Zhou

Medical image segmentation is a challenging problem. In this paper, a new automatic approach for MR brain image segmentation is presented. It is based on properties of Gauss-Hermite moments (GHMs) and fuzzy c-means (FCM).First, GHMs filter and GHMs detection are introduced and applied to image in preprocessing stage. FCM then performs to segment white matter (WM) and gray matter (GM). Subsequently, subtraction on GHMs detection is utilized to extract cerebrospinal fluid (CSF). Finally, examples on T1-weighted MR brain image are presented and show the efficiency of this approach.

Published in:

Visual Information Engineering, 2008. VIE 2008. 5th International Conference on

Date of Conference:

July 29 2008-Aug. 1 2008