Brain MR image segmentation with spatial constrained K-mean algorithm and dual-tree complex wavelet transform

Journal of Medical Systems

Volumn 38, Issue 9, 2014, Pages

  Zhang, Jingdan ^a   Jiang, Wuhan ^b   Wang, Ruichun ^a   Wang, Le ^a  

^a SHENZHEN INSTITUTE OF INFORMATION TECHNOLOGY   (China)

^b Department of Basic Public Course Shenzhen Institute of Information Technology ^*  (China)

Author keywords

Dual tree complex wavelet transform; K mean algorithm; Medical image segmentation; MR images

Indexed keywords

ALGORITHM; ANALYTIC METHOD; ARTICLE; DIAGNOSTIC IMAGING; DIFFUSION WEIGHTED IMAGING; DUAL TREE COMPLEX WAVELET TRANSFORM; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSING; INFORMATION PROCESSING; LOW FREQUENCY NOISE; MATHEMATICAL ANALYSIS; MATHEMATICAL PHENOMENA; NEUROIMAGING; NOISE MEASUREMENT; NUCLEAR MAGNETIC RESONANCE IMAGING; RADIOLOGICAL PARAMETERS; SPATIAL ANALYSIS; SPATIAL CONSTRAINED K MEAN ALGORITHM; WAVELET ANALYSIS; IMAGE ENHANCEMENT; PROCEDURES;

ALGORITHMS; HUMANS; IMAGE ENHANCEMENT; MAGNETIC RESONANCE IMAGING; NEUROIMAGING; WAVELET ANALYSIS;

EID: 84905560701     PISSN: 01485598     EISSN: 1573689X     Source Type: Journal    
DOI: 10.1007/s10916-014-0093-2     Document Type: Article

References (20)

1. Sahoo, P. K., Soltani, S., and Wong, A. K. C., A survey of thresholding techniques. Comput Vis Grap Imag Process 41:233-260, 1988.
2. Al-Naami, B., Bashir, A., Amasha, H., Al-Nabulsi, J., and Almalty, A. M., Statistical Approach for Brain Cancer Classification Using a Region Growing Threshold. J Med Sys 35:463-471, 2011.
3. Sainju, S., Bui, F. M., and Wahid, K. A., Automated Bleeding Detection in Capsule Endoscopy Videos Using Statistical Features and Region Growing. J Med Sys 38:25, 2014.
4. Egger, J., Colen, R. R., et al., Manual Refinement System for Graph-Based Segmentation Results in the Medical Domain. J Med Sys 36:2829-2839, 2012.
5. Chen, S. T., Hung, P. K., Lin, M. S., Huang, C. Y., Chen, M. C., Wang, T. D., and Lee, W. J., DWT-Based Segmentation Method for Coronary Arteries. J Med Sys 38:55, 2014.
6. Osareh, A., and Shadgar, B., A Segmentation Method of Lung Cavities Using Region Aided Geometric Snakes. J Med Sys 34:419-433, 2010.
7. Kannan, S. R., Ramathilagam, S., et al., Improved Fuzzy Clustering Algorithms in Segmentation of DC-enhanced breast MRI. J Med Sys 36:321-333, 2012.
8. Ubeyli, E. D., and Dogdu, E., Automatic Detection of Erythemato-Squamous Diseases Using k-Means Clustering. J Med Sys 34:179-184, 2010.
9. Avci, D., Leblebicioglu, M. K., Poyraz, M., and Dogantekin, E., A New Method Based on Adaptive Discrete Wavelet Entropy Energy and Neural Network Classifier (ADWEENN) for Recognition of Urine Cells from Microscopic Images Independent of Rotation and Scaling. J Med Sys 38:7, 2014.
10. Teng, W. G., and Chang, P. L., Identifying Regions of Interest in Medical Images Using Self-Organizing Maps. J Med Sys 36:2761-2768, 2012.
11. Reddick, W. E., Glass, J. O., et al., Automated segmentation and classification of multispectral magnetic resonance images of brain using artificial neural networks. IEEE Trans Med Imag 16:911-918, 1997. (Pubitemid 127770450)
12. Song, T., Gasparovic, C., et al., A hybrid tissue segmentation approach for brain MR images. Med Biol Eng Comput 44:242-249, 2006. (Pubitemid 43949718)
13. Chen, Y. J., Zhang, J. W., and Macione, J., An improved level set method for brain MR images segmentation and bias correction. Comput Med Imag Grap 33:510-519, 2009.
14. Kingsbury, N. G., Complex wavelets for shift invariant analysis and filtering of signals. Journal of Applied and Computational Harmonic Analysis 10(3):234-253, 2001.
15. Coifman, R. R., and Donoho, D. L., Translation-invariant de-noising. Lecture Notes in Statistics: Wavelets and Statistics 103:125-150, 1995.
16. Ma, J. W., Towards artifact-free characterization of surface topography using complex wavelets and total variation minimization. Appl Math Comput 170:1014-1030, 2005.
17. Leemput, K. V., Maes, F., Vandermeulen, D., and Suetens, P., Automatic model-based tissue classification of MR images of the brain. IEEE Trans Med Imag 18:897-908, 1999. (Pubitemid 32211105)
18. Warfield, S. K., Kaus, M., Jolesz, F. A., and Kikinis, R., Adaptive, template moderated, spatially varying statistical classification. Med Image Anal 4:43-55, 2000.
19. Dice, L. R., Measures of the amount of ecologic association between species. Ecology 26(3):297-302, 1945.
20. Duda, R. O., Hart, P. E., and Stork, D. G., Pattern Classification. Wiley, New York, 2001.