Browse > Article
http://dx.doi.org/10.9717/kmms.2014.17.12.1412

Implementation of 2D Snake Model-based Segmentation on Corpus Callosum  

Shidaifat, Ala'a ddin Al (Department of Computer Engineering, UHRC, Inje University)
Choi, Heung-Kook (Department of Computer Engineering, UHRC, Inje University)
Publication Information
Journal of Korea Multimedia Society / v.17, no.12, 2014 , pp. 1412-1417 More about this Journal
Abstract
The corpus callosum is the largest part of the brain, which is related to many neurological diseases. Snake model or active contour model is widely used in medical image processing field, especially image segmentation they look into the nearby edge, localizing them accurately. In this paper, corpus callosum segmentation using the snake model, is proposed. We tested a snake model on brain MRI. Then we compared the result with an active shape approach and found that snake model had better segmentation accuracy also faster than active shape approach.
Keywords
Corpus Callosum; Snake; Active Shape Approach; Segmentation;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 M.S. Keshavan, V.A. Diwadkar, K. Harenski, D.R. Rosenberg, J.A. Sweeney, and J.W. Pettegrew, "Abnormalities of the Corpus Callosum in First Episode, Treatment Naive Schizophrenia," Journal of Neurology, Neurosurgery and Psychiatry, Vol. 72, No. 6, pp. 757-760, 2002.   DOI
2 N. Sengee, A. Sengee, A. Enkhbolor, and H.K. Choi, "Contrast Enhancement for Segmentation of Hippocampus on Brain MR Images," Journal of Korea Multimedia Society, Vol. 15, No. 12, pp. 1409-1416, 2012.   과학기술학회마을   DOI   ScienceOn
3 F.L. Seixas, A.S.D. Souza, A.A.S. Santos, and D.C.M. Saade, "Automated Segmentation of the Corpus Callosum Midsagittal Surface Area," IEEE Conference on Computer Graphics and Image Processing, pp. 287-293, 2007.
4 R. Schonmeyer, M. Athelogou, A.R. Jagiela, C. Haenschel, and D.E.J. Linden, Fully Automated Segmentation of Corpus Callosum from Sagittal MRT Images, Definiens the Tissue Phenomics Company, Munich, Germany, SPL-0006-01-260208.
5 P. Freitas, L. Appenzeller, and R. Lotufo, "Watershed-Based Segmentation of the Midsagittal Section of the Corpus Callosum in Diffusion MRI," IEEE Conference on Graphics, Patterns and Images, pp. 274-280, 2011.
6 M.R.N. Zadeh, S. Saksena, A.B. Fermi, Q. Jiang, H.S. Zadeh, M. Rosenblum, et al., "Segmentation of Corpus Callosum using Diffusion Tensor Imaging: Validation in Patients with Glioblastoma," BMC Medical Imaging, Vol. 12, No. 10, pp. 1471-2342, 2012.
7 T.F. Cootes, C.J. Taylor, D.H. Cooper, and J. Graham, "Active Shape Models-Their Training And Application," Computer Vision and Image Understanding, Vol. 61, No. 1, pp. 38-59, 1995.
8 M. Kass, A. Witkin, and D. Terzpoulos, "Snakes: Active Contour Models," International Journal of Computer Vision, Vol. 1, No. 4, pp. 321-331, 1988.   DOI   ScienceOn
9 B. Ostlad and A. Tonp, "Encoding of a Priori Information in Active Contour Models," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 18, No. 9, pp. 863-872, 1996.   DOI
10 S.C. Zhu and A. Yuille, "Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation," IEEE Transations on Pattern Analysis and Machine Intelligence, Vol. 18, No. 9, pp. 884-900, 1996.   DOI   ScienceOn
11 C. Xu and J. Prince, "Snakes, Shapes, and Gradient Vector Flow," IEEE Transactions on Image Processing, Vol. 7, No. 3, pp. 359-369, 1998.   DOI   ScienceOn
12 C. Held, R. Palmisano, L. Haberle, and T. Wittenberg, "Comparison of Parameteradapted Segmentation Methods for Fluorescence Micrographs," Cytometry Part A., Vol. 79, No. 11, pp. 933-945, 2011.
13 ITK-SNAP, http://www.itksnap.org (Accessed: 22 February 2013).
14 A. Enkhbolor, Y.S. Izmantoko, and H.K. Choi, "Comparison of Active Contour and Active Shape Approaches for Corpus Callosum Segmentation," Journal of Korea Multimedia Society, Vol. 16, No. 9, pp. 1018-1030, 2013.   과학기술학회마을   DOI   ScienceOn