Detection of Alzheimer's disease and mild cognitive impairment based on structural volumetric MR images using 3D-DWT and WTA-KSVM trained by PSOTVAC

Biomedical Signal Processing and Control

Volumn 21, Issue , 2015, Pages 58-73

  Zhang, Yudong ^a,b   Wang, Shuihua ^a   Phillips, Preetha ^c   Dong, Zhengchao ^b   Ji, Genlin ^a,b   Yang, Jiquan ^a  

^a NANJING NORMAL UNIVERSITY   (China)

^b NEW YORK STATE PSYCHIATRIC INSTITUTE   (United States)

^c SHEPHERD UNIVERSITY   (United States)

Author keywords

Kernel SVM; Magnetic resonance imaging; Multiclass SVM; Particle swarm optimization; Time varying acceleration coefficient

Indexed keywords

CLASSIFICATION (OF INFORMATION); DIAGNOSIS; DIRECTED GRAPHS; DISCRETE WAVELET TRANSFORMS; NEURODEGENERATIVE DISEASES; PARTICLE SWARM OPTIMIZATION (PSO); SIGNAL RECONSTRUCTION; SUPPORT VECTOR MACHINES;

DIRECTED ACYCLIC GRAPH (DAG); KERNEL SVM; MILD COGNITIVE IMPAIRMENTS; MILD COGNITIVE IMPAIRMENTS (MCI); MULTICLASS SVM; PRINCIPLE COMPONENT ANALYSIS; STATE-OF-THE-ART METHODS; TIME-VARYING ACCELERATION COEFFICIENTS;

MAGNETIC RESONANCE IMAGING;

AGED; ALZHEIMER DISEASE; ARTICLE; CLASSIFIER; CLINICAL DEMENTIA RATING; COMPARATIVE STUDY; CONTROLLED STUDY; DECOMPOSITION; DIAGNOSTIC ACCURACY; EARLY DIAGNOSIS; FEMALE; GENETIC ALGORITHM; HUMAN; KERNEL METHOD; LINEAR SUPPORT VECTOR MACHINE; MACHINE LEARNING; MAJOR CLINICAL STUDY; MALE; MATHEMATICAL MODEL; MILD COGNITIVE IMPAIRMENT; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY; PATTERN RECOGNITION; PRIORITY JOURNAL; RADIOLOGICAL PARAMETERS; SENESCENCE; SUPPORT VECTOR MACHINE; THREE DIMENSIONAL DISCRETE WAVELET TRANSFORM; THREE DIMENSIONAL IMAGING;

EID: 84931263154     PISSN: 17468094     EISSN: 17468108     Source Type: Journal    
DOI: 10.1016/j.bspc.2015.05.014     Document Type: Article

References (46)

1. K. Hahn, N. Myers, S. Prigarin, K. Rodenacker, A. Kurz, H. Förstl, C. Zimmer, A.M. Wohlschläger, and C. Sorg Selectively and progressively disrupted structural connectivity of functional brain networks in Alzheimer's disease - revealed by a novel framework to analyze edge distributions of networks detecting disruptions with strong statistical evidence NeuroImage 81 2013 96 109
2. R. Brookmeyer, E. Johnson, K. Ziegler-Graham, and H.M. Arrighi Forecasting the global burden of Alzheimer's disease Alzheimer's Dementia 3 2007 186 191 (the journal of the Alzheimer's Association)
3. J.W. Han, T.H. Kim, S.B. Lee, J.H. Park, J.J. Lee, Y. Huh, J.E. Park, and K.W. Kim Predictive validity and diagnostic stability of mild cognitive impairment subtype Asian J. Psychiatry 4, Supplement 1 2011 S65 S66
4. Y. Zhang, S. Wang, G. Ji, and Z. Dong Exponential wavelet iterative shrinkage thresholding algorithm with random shift for compressed sensing magnetic resonance imaging IEEJ Trans. Electr. Electron. Eng. 10 2015 116 117
5. S. Goh, Z. Dong, Y. Zhang, S. DiMauro, and B.S. Peterson Mitochondrial dysfunction as a neurobiological subtype of autism spectrum disorder: evidence from brain imaging JAMA Psychiatry 71 2014 665 671
6. Z. Dong, Y. Zhang, F. Liu, Y. Duan, A. Kangarlu, and B.S. Peterson Improving the spectral resolution and spectral fitting of 1H MRSI data from human calf muscle by the SPREAD technique NMR Biomed. 27 2014 1325 1332
7. T. Kubota, Y. Ushijima, and T. Nishimura A region-of-interest (ROI) template for three-dimensional stereotactic surface projection (3D-SSP) images: initial application to analysis of Alzheimer disease and mild cognitive impairment Int. Congr. Ser. 1290 2006 128 134
8. C. Pennanen, M. Kivipelto, S. Tuomainen, P. Hartikainen, T. Hänninen, M.P. Laakso, M. Hallikainen, M. Vanhanen, A. Nissinen, E.-L. Helkala, P. Vainio, R. Vanninen, K. Partanen, and H. Soininen Hippocampus and entorhinal cortex in mild cognitive impairment and early AD Neurobiol. Aging 25 2004 303 310
9. W. Lee, B. Park, and K. Han Classification of diffusion tensor images for the early detection of Alzheimer's disease Comput. Biol. Med. 43 2013 1313 1320
10. S. Chaplot, L.M. Patnaik, and N.R. Jagannathan 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
11. E.S.A. El-Dahshan, T. Hosny, and A.B.M. Salem Hybrid intelligent techniques for MRI brain images classification Digital Signal Process. 20 2010 433 441
12. R. Ramasamy, and P. Anandhakumar Brain tissue classification of MR images using fast Fourier transform based expectation - maximization Gaussian mixture model Advances in Computing and Information Technology 2011 Springer Berlin 387 398
13. Y. Zhang, and L. Wu An MR brain images classifier via principal component analysis and kernel support vector machine Prog. Electromagnet. Res. 130 2012 369 388
14. A.P. Nanthagopal, and R.S. Rajamony Classification of benign and malignant brain tumor CT images using wavelet texture parameters and neural network classifier J. Vis. 16 2013 19 28
15. H. Kalbkhani, M.G. Shayesteh, and B. Zali-Vargahan Robust algorithm for brain magnetic resonance image (MRI) classification based on GARCH variances series Biomed. Signal Process. Control 8 2013 909 919
16. Y. Zhang, S. Wang, G. Ji, and Z. Dong Genetic pattern search and its application to brain image classification Math. Probl. Eng. 2013 2013 8
17. M. Saritha, K. Paul Joseph, and A.T. Mathew Classification of MRI brain images using combined wavelet entropy based spider web plots and probabilistic neural network Pattern Recognit. Lett. 34 2013 2151 2156
18. Y. Zhang, Z. Dong, G. Ji, and S. Wang Effect of spider web plot in MR brain image classification Pattern Recognit. Lett. 62 2015 14 16
19. S. Das, M. Chowdhury, and M.K. Kundu Brain MR image classification using multiscale geometric analysis of ripplet Prog. Electromagnet. Res. - PIER 137 2013 1 17
20. C.Z. En, and T.T. Swee Computer-aided knee osteoarthritis classification system using artificial neural network (ANN) J. Med. Imaging Health Inform. 3 2013 561 565
21. G. Vishnuvarthanan, and M. Pallikonda Rajasekaran Segmentation of MR brain images for tumor extraction using fuzzy Curr. Med. Imaging Rev. 9 2013 2 6
22. F. Falahati, E. Westman, and A. Simmons Multivariate data analysis and machine learning in Alzheimer's disease with a focus on structural magnetic resonance imaging J. Alzheimers Dis. 41 2014 685 708
23. Y. Zhang, S. Wang, and Z. Dong Classification of Alzheimer disease based on structural magnetic resonance imaging by kernel support vector machine decision tree Prog. Electromagnet. Res. 144 2014 171 184
24. A. Padma, and R. Sukanesh Segmentation and classification of brain CT images using combined wavelet statistical texture features Arab. J. Sci. Eng. 39 2014 767 776
25. E.S.A. El-Dahshan, H.M. Mohsen, K. Revett, and A.B.M. Salem Computer-aided diagnosis of human brain tumor through MRI: a survey and a new algorithm Expert Syst. Appl. 41 2014 5526 5545
26. J.X. Zou, M.J. Wang, X.J. Lei, and X.G. Chen 3.0 T MRI arterial spin labeling and magnetic resonance spectroscopy technology in the application of Alzheimer's disease Exp. Gerontol. 60 2014 31 36
27. Z.R. Luo, X.J. Zhuang, R.Z. Zhang, J.Q. Wang, C. Yue, and X. Huang Automated 3D segmentation of hippocampus based on active appearance model of brain MR images for the early diagnosis of Alzheimer's disease Minerva Med. 105 2014 157 165
28. R. Simoes, A.M.V. van Walsum, and C.H. Slump Classification and localization of early-stage Alzheimer's disease in magnetic resonance images using a patch-based classifier ensemble Neuroradiology 56 2014 709 721
29. X. Zhou, S. Wang, W. Xu, G. Ji, P. Phillips, P. Sun, and Y. Zhang Detection of pathological brain in MRI scanning based on Wavelet-entropy and Naive Bayes Classifier F. Ortuño, I. Rojas (Eds.), Bioinformatics and Biomedical Engineering 2015 Springer International Publishing Granada, Spain 201 209
30. Y. Zhang, Z. Dong, S. Wang, G. Ji, and J. Yang Preclinical diagnosis of magnetic resonance (MR) brain images via discrete wavelet packet transform with Tsallis entropy and generalized eigenvalue proximal support vector machine (GEPSVM) Entropy 17 2015 1795 1813
31. G. Yang, Y. Zhang, J. Yang, G. Ji, Z. Dong, S. Wang, C. Feng, and Q. Wang Automated classification of brain images using wavelet-energy and biogeography-based optimization Multimedia Tools Appl. 2015 1 17
32. X. Chen, W. Yang, Z. He, and W. Zhong Adaptive acquisition footprint suppression based on a 3D stationary wavelet transform: a case study from China J. Appl. Geophys. 77 2012 1 6
33. A.F. Fotenos, A.Z. Snyder, L.E. Girton, J.C. Morris, and R.L. Buckner Normative estimates of cross-sectional and longitudinal brain volume decline in aging and AD Neurology 64 2005 1032 1039
34. L. Fang, L. Wu, and Y. Zhang A novel demodulation system based on continuous wavelet transform Math. Probl. Eng. 2015 2015 9
35. S. Zu'bi, N. Islam, and M. Abbod 3D multiresolution analysis for reduced features segmentation of medical volumes using PCA Circuits and Systems (APCCAS), 2010 IEEE Asia Pacific Conference on 2010 604 607
36. M. Kuroda, Y. Mori, M. Iizuka, and M. Sakakihara Acceleration of the alternating least squares algorithm for principal components analysis Comput. Stat. Data Anal. 55 2011 143 153
37. Y. Zhang, S. Wang, G. Ji, and Z. Dong An MR brain images classifier system via particle swarm optimization and kernel support vector machine Sci. World J. 2013 2013 9
38. K.P. Wu, and S.D. Wang Choosing the kernel parameters for support vector machines by the inter-cluster distance in the feature space Pattern Recognit. 42 2009 710 717
39. O.P. Dewhirst, N. Angarita-Jaimes, D.M. Simpson, R. Allen, and P.L. Newland A system identification analysis of neural adaptation dynamics and nonlinear responses in the local reflex control of locust hind limbs J. Comput. Neurosci. 34 2013 39 58
40. C.J.A. Bastos, D.A.R. Chaves, F. Silva, H.A. Pereira, and J.F. Martins Wavelength assignment for physical-layer-impaired optical networks using evolutionary computation J. Opt. Commun. Netw. 3 2011 178 188
41. R.E. Precup, R.C. David, E.M. Petriu, S. Preitl, and M.B. Radac Fuzzy control systems with reduced parametric sensitivity based on simulated annealing IEEE Trans. Ind. Electron. 59 2012 3049 3061
42. M.Z. Ali, K. Alkhatib, and Y. Tashtoush Cultural algorithms: emerging social structures for the solution of complex optimization problems Int. J. Artif. Intell. 11 2013 20 42
43. Y. Zhang, S. Wang, P. Phillips, and G. Ji Binary PSO with mutation operator for feature selection using decision tree applied to spam detection Knowl. Based Syst. 64 2014 22 31
44. P. Lingras, and C. Butz Rough set based 1-v-1 and 1-v-r approaches to support vector machine multi-classification Inf. Sci. 177 2007 3782 3798
45. J.C. Platt, N. Cristianini, and J. Shawe-Taylor Large margin DAGs for multiclass classification Adv. Neural Inf. Process. Syst. 12 2000 547 553
46. Y. Zhang, S. Wang, G. Ji, and P. Phillips Fruit classification using computer vision and feedforward neural network J. Food Eng. 143 2014 167 177