DocumentCode :
2273530
Title :
Lungs image segmentation through weighted FCM
Author :
Sivakumar, S. ; Chandrasekar, C.
Author_Institution :
Dept. of Comput. Sci., Periyar Univ., Salem, India
fYear :
2012
fDate :
25-27 April 2012
Firstpage :
109
Lastpage :
113
Abstract :
Image processing is an essential technique for analyzing images. The important part of image processing is image segmentation. Segmentation is a task of grouping pixels based on similarity. In medical image analysis, segmentation is very important phase. In this paper standard FCM and weighted FCM segmentation algorithms are discussed. Experiments are carried out on LIDC medical images to examine the performance of the standard FCM and the proposed weighted FCM technique. The results are compared with various validation measures to explore the accuracy of our proposed approach.
Keywords :
fuzzy set theory; image segmentation; lung; medical image processing; LIDC medical images; image processing; lungs image segmentation; medical image analysis; weighted FCM; weighted fuzzy C-means; Cancer; Clustering algorithms; Computed tomography; Image segmentation; Indexes; Lungs; Object segmentation; FCM; Haralick features; Image segmentation; Validation measures; Weighted FCM;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Recent Advances in Computing and Software Systems (RACSS), 2012 International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4673-0252-4
Type :
conf
DOI :
10.1109/RACSS.2012.6212707
Filename :
6212707
Link To Document :
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