By Topic

Study on the Application of MRF and Fuzzy Clustering as Well as the D-S Theory to Image Fusion Segmentation of the Human Brain

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 $13
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

5 Author(s)
Yi-Hong Guan ; Fac. of Sci., Kunming Univ. of Sci. & Technol., Kunming, China ; Yatao Luo ; Tao Yang ; Lei Qiu
more authors

The features of the spatial information of Markov random field image was used in image segmentation. It can effectively remove the noise, so that more accurate segmentation results can be obtained. And more satisfactory segmentation results can be achieved with the application of Fuzzy Clustering Theory together with Two-Dimensional Histogram image segmentation methods, However, these two ways leads to different classification results while classifying the controversial pixels in images, so we can use the Dempster-Shafer evidence theory to fuse multi-source information, to assign the controversial points to the plausibility interval, and then divide them. This paper will adopt the above three theories to propose a new human brain image segmentation method. Experimental result shows that the segmentation result is more in line with human vision, and is of vital significance to accurate analysis and application of tissues.

Published in:

Intelligent Networks and Intelligent Systems (ICINIS), 2011 4th International Conference on

Date of Conference:

1-3 Nov. 2011