Research of Brain MRI image segmentation algorithm based on FCM and SVM

Author

Jun Xiao ; Yifan Tong

Author_Institution

Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China

fYear

2014

fDate

May 31 2014-June 2 2014

Firstpage

1712

Lastpage

1716

Abstract

Brain disease is one of common diseases that threaten human health, which is becoming one of hot researches in society and medical profession. After a variety of image segmentation methods in the brain MR image segmentation are studied, it is found that FCM algorithm and SVM algorithm have a lot of advantages and good application prospection. Then a combination of unsupervised classification algorithm of FCM and fuzzy support vector machine model is proposed and the segmentation accuracy in the image with high noise and high bias fields is tested. Experimental results prove the validity of the proposed algorithm.

Keywords

biomedical MRI; brain; image segmentation; medical signal processing; pattern clustering; support vector machines; FCM algorithm; SVM algorithm; brain MRI image segmentation algorithm; brain disease; fuzzy C-means clustering algorithm; fuzzy support vector machine model; Clustering algorithms; Estimation; Image segmentation; Medical diagnostic imaging; Noise; Support vector machines; Brain MRI; Image segmentation; SVM;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (2014 CCDC), The 26th Chinese

Conference_Location

Changsha

Print_ISBN

978-1-4799-3707-3

Type

conf

DOI

10.1109/CCDC.2014.6852445

Filename

6852445