Home   >   CSC-OpenAccess Library   >    Manuscript Information
Brain Tumor Extraction from T1- Weighted MRI using Co-clustering and Level Set Methods
S.Satheesh, K.V.S.V.R Prasad, K.Jitender Reddy
Pages - 219 - 226     |    Revised - 05-04-2013     |    Published - 30-04-2013
Volume - 7   Issue - 2    |    Publication Date - April 2013  Table of Contents
MORE INFORMATION
KEYWORDS
Magnetic Resonance Imaging, Tumor Extraction, Co-clustering Method, Level Set Method.
ABSTRACT
The aim of the paper is to propose effective technique for tumor extraction from T1-weighted magnetic resonance brain images with combination of co-clustering and level set methods. The co-clustering is the effective region based segmentation technique for the brain tumor extraction but have a drawback at the boundary of tumors. While, the level set without re-initialization which is good edge based segmentation technique but have some drawbacks in providing initial contour. Therefore, in this paper the region based co-clustering and edge-based level set method are combined through initially extracting tumor using co-clustering and then providing the initial contour to level set method, which help in cancelling the drawbacks of co-clustering and level set method. The data set of five patients, where one slice is selected from each data set is used to analyze the performance of the proposed method. The quality metrics analysis of the proposed method is proved much better as compared to level set without re-initialization method.
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 Scribd 
5 SlideShare 
6 PdfSR 
Chen Ting, Dimitris Metaxas., “A hybrid framework for 3D medical image segmentation,”Medical Image Analysis, Volume 9, Issue 6, Pages 547-565, December 2005.
Chen, Yunjie; Zhang, Jianwei; Pheng-Ann Heng; Xia, Deshen, "Chinese Visible Human Brain Image Segmentation," Image and Signal Processing, 2008. CISP '08. Congress on , vol.3,no., pp.639,643, 27-30 May 2008.
Chunming Li; Chenyang Xu; Changfeng Gui; Fox, M.D., "Level set evolution without reinitialization:a new variational formulation," Computer Vision and Pattern Recognition, 2005.CVPR 2005. IEEE Computer Society Conference on , vol.1, no., pp.430,436 vol. 1, 20-25 June 2005.
Dhillon, Inderjit S “Co-clustering documents and words using bipartite spectral graph partitioning”. Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining -KDD '01, San Francisco, California,pages: 269--274,2001.
Ho, S.; Bullitt, E.; Gerig, G., "Level-set evolution with region competition: automatic 3-D segmentation of brain tumors," Pattern Recognition, 2002. Proceedings. 16th International Conference on , vol.1, no., pp.532,535 vol.1, 2002.
Hongyu Lu; Youming Yu; Shanglian Bao, "Note: On modeling techniques in active contours," Signal Processing (ICSP), 2012 IEEE 11th International Conference on , vol.2, no.,pp.956,961, 21-25 Oct. 2012.
Law, A.K.W.; Hui Zhu; Chan, B.C.B.; Iu, P. P.; Lam, F. K.; Chan, F.H.Y., "Semi-automatic tumor boundary detection in MR image sequences," Intelligent Multimedia, Video and Speech Processing, 2001. Proceedings of 2001 International Symposium on , vol., no., pp.28,31,2001.
Li, Danyi; Li, Weifeng; Liao, Qingmin, "Active contours driven by local probability distributions," Image and Signal Processing (CISP), 2012 5th International Congress on , vol.,no., pp.634,638, 16-18 Oct. 2012.
Malladi, R.; Sethian, J.A.; Vemuri, B.C., "Shape modeling with front propagation: a level set approach," Pattern Analysis and Machine Intelligence, IEEE Transactions on , vol.17, no.2,pp.158,175, Feb 1995.
Osher Stanley, Sethian James A., “Fronts propagating with curvature-dependent speed:Algorithms based on Hamilton-Jacobi formulations,” Journal of Computational Physics,Volume 79, Issue 1,pp. 12-49, , November 1988.
Rege, M.; Ming Dong; Fotouhi, F., "Co-clustering Documents and Words Using Bipartite Isoperimetric Graph Partitioning," Data Mining, 2006. ICDM '06. Sixth International Conference on , vol., no., pp.532,541, 18-22 Dec. 2006.
S.Satheesh, Dr.K.V.S.V.R Prasad, Dr.K.Jitender Reddy; “Automatic tumor extraction for contrast enhanced axial T1-weighted magnetic resonance brain images integrating coclustering and morphological operations”, International Conference on Signal, Image and Video Processing (ICSIVP), IITPatna , pp.214-218,January -2012.
Si Yong Yeo, "Implicit active contours for N-dimensional biomedical image segmentation," Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on , vol., no., pp.2855,2860, 14-17 Oct. 2012.
Taheri, S.; Sim Heng Ong; Chong, V., "Threshold-based 3D Tumor Segmentation using Level Set (TSL)," Applications of Computer Vision, 2007. WACV '07. IEEE Workshop on , vol., no.,pp.45,45, Feb. 2007.
Verma, N.; Muralidhar, G.S.; Bovik, A.C.; Cowperthwaite, M.C.; Markey, M.K., "Model-driven,probabilistic level set based segmentation of magnetic resonance images of the brain," Engineering in Medicine and Biology Society,EMBC, 2011 Annual International Conference of the IEEE , vol., no., pp.2821,2824, Aug. 30 2011-Sept. 3 2011.
Yan Zhu; Hong Yan, "Computerized tumor boundary detection using a Hopfield neural network," Medical Imaging, IEEE Transactions on , vol.16, no.1, pp.55,67, Feb. 1997.
Mr. S.Satheesh
Dept. of ECE, G. Narayanamma Institute of Technology and Science, Hyderabad, India. - India
satheesh.s17@gmail.com
Dr. K.V.S.V.R Prasad
Dept. of ECE, D.M.S.S.V.H. College of Engineering, Machilipatnam, India. - India
Dr. K.Jitender Reddy
Dept. of Radiology and Imaging Sciences, Apollo Health City, Hyderabad, India. - India


CREATE AUTHOR ACCOUNT
 
LAUNCH YOUR SPECIAL ISSUE
View all special issues >>
 
PUBLICATION VIDEOS