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International Journal of Scientific and Engineering Research
ISSN Online 2229-5518
ISSN Print: 2229-5518 6    
Website: http://www.ijser.org
scirp IJSER >> Volume 3,Issue 6,June 2012
A Proposed technique for Brain MRI Using Region Based Segmentation
Full Text(PDF, )  PP.13-16  
Harman Kataria, Alka Jindal
Active Contour, Segmentation, Intensity Inhomogenity, Magnetic Resonance Image (MRI), Level Set Method, Local Region based Active contour
The paper presents an efficient brain MRI region based segmentation technique that accurately classifies the abnormal tissue from normal tissue. All methods are used for noisy and blurred images and perform segmentation in improved way. A comparison of three different brain MRI segmentation methods, viz., improved level segmentation method, local region based active contour and variational level set formulation method along with their comparison and their results.These methods are applied on both 2d as well as 3d images
[1] Wang Rongfu, PET/CT Tumour Diagonsis, 1st ed., Peking University Medical Press, Beijing, 2007, pp.3-13.(in Chinese)

[2] V.Caselles, R. Kimmel, and G. Sapiro,”Geodesic active contour”,Int. J. Comput. Vis, vol. 22, pp.61-79, 1997. [3] T. Chan and L. Vese,” Active contour without edges,” IEEE trans Image Process., vol. 10, no. 2, pp 266-277, Feb. 2001.

[4] Jia Di, Yang Jin-Zhu, Zhang Yi-Fei. “An Efficient Modified Level Set Method For Brain Tissue Segmentation”, IEEE International Conference on Information and Automation june 2010.

[5]. Shawn Lankton, Allen Tannenbaum, “Localizing Region-Based Active Contours,” IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 17, NO. 11, NOVEMBER 2008.

[6] Chunming Li ,Chiu-Yen Kao and John C.Gore,”Minimization of Region-Scalable Fitting Energy for Image Segmentation”,IEEE Trans. On Image Processing, vol.17,n0. 10,October 2008.

[7] Z. Hou,”A review on mr image intensity inhomogenity correction,”Int. J. Biomed. Imag.,2006.

[8]. J. A. Yezzi, A. Tsai, and A.Willsky, “A fully global approach to image segmentation via coupled curve evolution equations,” J. Vis. Comm. Image Rep., vol. 13, no. 1, pp. 195–216, Mar. 2002.

[9] L. Vese and T. Chan, “A multiphase level set framework for image segmentation using the Mumford and Shah model, ”Int.J.Comput.Vis.,vol. 50, pp. 271–293, 2002.

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