Title :
A fast and noise-adaptive rough-fuzzy hybrid algorithm for medical image segmentation
Author :
Srivastava, Arpit ; Asati, Abhinav ; Bhattacharya, Mahua
Author_Institution :
Dept. of Electron. & Commun., Mualana Azad Nat. Inst. of Technol., Bhopal, India
Abstract :
An Accurate, Fast and Noise-Adaptive segmentation of Brain MR Images for clinical Analysis is a challenging problem. An improved Hybrid Clustering Algorithm is presented here, which integrates the concept of recently popularized Rough Sets and that of Fuzzy Sets. The concept of lower and upper approximations of rough sets is incorporated to handle uncertainty, vagueness, and incompleteness in class definition. For making the segmentation robust to Noise and intensity in-homogeneity, the images are proposed to be pre-processed with a neighbourhood averaging spatial filter. To accelerate the segmentation process, a novel Suppressed Rough Fuzzy C-Means model is presented in which a membership suppression mechanism has been implemented, which creates competition among clusters to speed-up the clustering process. The effectiveness of the presented algorithm along with comparison with other related algorithm has been demonstrated on a set of MR and CT scan images. The results using MRI data show that our method provides better results compared to standard Fuzzy C-Means based algorithms and other modified similar techniques.
Keywords :
biomedical MRI; brain; fuzzy set theory; image segmentation; medical image processing; pattern clustering; rough set theory; Suppressed Rough Fuzzy C-Means model; brain MR image; fuzzy set; hybrid clustering algorithm; incompleteness; medical image segmentation; membership suppression mechanism; noise adaptive rough fuzzy hybrid algorithm; rough set; uncertainty; vagueness; Approximation methods; Clustering algorithms; Image segmentation; Indexes; Magnetic resonance imaging; Noise; Rough sets; Clustering; Fuzzy C-Means; Image Segmentation; Medical Images; Rough Sets;
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2010 IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-8306-8
Electronic_ISBN :
978-1-4244-8307-5
DOI :
10.1109/BIBM.2010.5706602