DocumentCode :
230927
Title :
Automatic brain MRI image segmentation using FCM and LSM
Author :
Singh, Prashant ; Bhadauria, H.S. ; Singh, Ashutosh
Author_Institution :
Dept. of Comput. Sci. & Eng., G.B. Pant Eng. Coll., Pauri Garhwal, India
fYear :
2014
fDate :
8-10 Oct. 2014
Firstpage :
1
Lastpage :
6
Abstract :
The significant objective of this paper is to produce a method that is able to delineate the object of interest or tumor region easily from the available brain MRI images. This is attained by the unification of the fuzzy c-means clustering and level set method. The method proposed performs the segmentation by smoothly exploiting the spatial function during FCM clustering. Since, we are utilizing the FCM which could prove the automaticity of the method by dividing the original image into clusters and then using one cluster for automatic initialization. This in turn helps in making the whole processing less tedious with reducing the time as well. Thereby, if considered it could be competent tool in future. Secondly, to find the contour of tumor region in the original image the proposed method uses the level set method which comes in handy in situations where the topologies of the images changes frequently by merging or splitting in two. Also, the proposed methodology makes use of variational level method in place of generic level set method which in turn eliminates one more flaw of re- initializing the contour during segmentation. When we are using the segmentation methods which are manual then it can lead to a situation where different medical experts generate different results which can also overcome by using the proposed approach.
Keywords :
biomedical MRI; brain; fuzzy set theory; medical image processing; tumours; FCM clustering; LSM; automatic brain MRI image segmentation; fuzzy c-means clustering; level set method; spatial function; tumor region; variational level method; Biomedical imaging; Clustering algorithms; Image segmentation; Level set; Magnetic resonance imaging; Shape; Tumors; Fuzzy c-means; Image segmentation; defuzzification; level set methods; variational level sets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions), 2014 3rd International Conference on
Conference_Location :
Noida
Print_ISBN :
978-1-4799-6895-4
Type :
conf
DOI :
10.1109/ICRITO.2014.7014706
Filename :
7014706
Link To Document :
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