Hybrid intelligent techniques for MRI brain images classification

Digital Signal Processing: A Review Journal

Volumn 20, Issue 2, 2010, Pages 433-441

  El Dahshan, El Sayed Ahmed ^a   Hosny, Tamer ^b   Salem, Abdel Badeeh M ^c  

^a Ain Shams University   (Egypt)

^b Misr University for Science and Technology   (Egypt)

^c Ain Shams University   (Egypt)

Author keywords

Classification; Hybrid intelligent techniques; k Nearest neighbors; MRI human brain images; Neural computing; Wavelet transformation

Indexed keywords

BACKPROPAGATION; BRAIN MAPPING; CLASSIFICATION (OF INFORMATION); DISCRETE WAVELET TRANSFORMS; IMAGE COMPRESSION; MAGNETIC RESONANCE; MAGNETIC RESONANCE IMAGING; MEMBERSHIP FUNCTIONS; MOTION COMPENSATION; NEAREST NEIGHBOR SEARCH; NEURAL NETWORKS; PRINCIPAL COMPONENT ANALYSIS; TEXT PROCESSING;

HUMAN BRAIN; INTELLIGENT TECHNIQUES; K-NEAREST NEIGHBORS; NEURAL COMPUTING; WAVELET TRANSFORMATIONS;

IMAGE CLASSIFICATION;

EID: 76549108474     PISSN: 10512004     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.dsp.2009.07.002     Document Type: Article

References (19)

1. Fletcher-Heath L.M., Hall L.O., Goldgof D.B., and Murtagh F.R. Automatic segmentation of non-enhancing brain tumors in magnetic resonance images. Artif. Intell. Med. 21 (2001) 43-63
2. Chaplot S., Patnaik L.M., and Jagannathan N.R. Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network. Biomed. Signal Process. Control 1 (2006) 86-92
3. Gorunescu F. Data mining techniques in computer-aided diagnosis: Non-invasive cancer detection. PWASET 25 (2007) 427-430
4. Kara S., and Dirgenali F. A system to diagnose atherosclerosis via wavelet transforms, principal component analysis and artificial neural networks. Expert Syst. Appl. 32 (2007) 632-640
5. Maitra M., and Chatterjee A. Hybrid multiresolution Slantlet transform and fuzzy c-means clustering approach for normal-pathological brain MR image segregation. Med. Eng. Phys. (2007) 10.1016/j.medengphy.2007.06.009
6. Karibasappa K., and Patnaik S. Face recognition by ANN using wavelet transform coefficients. IE (India) J. Computer Eng. 85 (2004) 17-23
7. Hiremath P.S., Shivashankar S., and Pujari J. Wavelet based features for color texture classification with application to CBIR. Int. J. Computer Sci. Network Sec. 6 9A (2006) 124-133
8. Daubechies I. Ten Lectures on Wavelets. Reg. Conf. Ser. in Appl. Math. (1992), SIAM, Philadelphia, PA
9. Sengur A. An expert system based on principal component analysis, artificial immune system and fuzzy k-NN for diagnosis of valvular heart diseases. Comp. Biol. Med. (2007) 10.1016/j.compbiomed.2007.11.004
10. Roy K., and Bhattacharya P. Optimal features subset selection and classification for Iris recognition. J. Image Video Process. (2008) 10.1155/2008/743103
11. Bouchaffra D., and Tan J. Structural hidden Markov models for biometrics: Fusion of face and fingerprint. Pattern Recogn. 41 (2008) 852-867
12. M. Kocionek, A. Materka, M. Strzelecki, P. Szczypiński, Discrete wavelet transform - derived features for digital image texture analysis, in: Proc. of International Conference on Signals and Electronic Systems, Lodz, Poland, 18-21 September 2001, pp. 163-168
13. Jain A.K., Duin R.P.W., and Mao J. Statistical pattern recognition: A review. IEEE Trans. Pattern Anal. Mach. Intell. 22 (2000) 4-37
14. Duda R.O., Hart P.E., and Stork D.G. Pattern Classification (2001), Wiley, New York
15. Latifoglu F., Polat K., Kara S., and Gunes S. Medical diagnosis of atherosclerosis from carotid artery Doppler signals using principal component analysis (PCA), k-NN based weighting pre-processing and Artificial Immune Recognition System (AIRS). J. Biomed. Inform. 41 (2008) 15-23
16. O'Farrell M., Lewis E., Flanagan C., and Jackman N. Comparison of k-NN and neural network methods in the classification of spectral data from an optical fibre-based sensor system used for quality control in the food industry. Sens. Actuators B: Chemical 111-112C (2005) 354-362
17. Haykin S. Neural Networks: A Comprehensive Foundation (1999), Prentice Hall
18. Harvard Medical School. Web. data available at. http://med.harvard.edu/AANLIB/
19. Polat K., Akdemir B., and Günȩs S. Computer aided diagnosis of ECG data on the least square support vector machine. Digital Signal Process. 18 (2008) 25-32