메뉴 건너뛰기




Volumn 16, Issue 1, 2017, Pages 5-10

A feature-free 30-disease pathological brain detection system by linear regression classifier

Author keywords

Linear regression classifier; Machine learning; Pathological brain detection; Pattern recognition

Indexed keywords

ALGORITHM; ALZHEIMER DISEASE; ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION NEURAL NETWORK; CEREBROVASCULAR DISEASE; DEGENERATIVE DISEASE; DIAGNOSTIC ACCURACY; DISEASE CLASSIFICATION; FUNCTIONAL NEUROIMAGING; HUMAN; INFLAMMATORY DISEASE; LEARNING VECTOR QUANTIZATION NEURAL NETWORK; LINEAR REGRESSION CLASSIFIER; MATHEMATICAL MODEL; MEASUREMENT ACCURACY; MEASUREMENT PRECISION; NEOPLASM; REVIEW; SENSITIVITY AND SPECIFICITY; AUTOMATION; BRAIN; DIAGNOSTIC IMAGING; FUZZY LOGIC; IMAGE PROCESSING; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; PSYCHOLOGY; REGRESSION ANALYSIS; REPRODUCIBILITY; STATISTICAL MODEL;

EID: 85011067770     PISSN: 18715273     EISSN: 19963181     Source Type: Journal    
DOI: 10.2174/1871527314666161124115531     Document Type: Review
Times cited : (26)

References (36)
  • 1
    • 84930332968 scopus 로고    scopus 로고
    • Preclinical diagnosis of magnetic resonance (MR) brain images via discrete wavelet packet transform with Tsallis entropy and generalized eigenvalue proximal support vector machine (GEPSVM)
    • Yang J. 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 2015; 17(4): 1795-13.
    • (2015) Entropy , vol.17 , Issue.4 , pp. 1795-1813
    • Yang, J.1
  • 2
    • 84957589192 scopus 로고    scopus 로고
    • Defining Core and Penumbra in Is-chemic Stroke: A Voxel-and Volume-Based Analysis of Whole Brain CT Perfusion
    • Yu Y, Han Q, Ding X, et al. Defining Core and Penumbra in Is-chemic Stroke: A Voxel-and Volume-Based Analysis of Whole Brain CT Perfusion. Sci Report 2016; 6; Article ID: 20932.
    • (2016) Sci Report , vol.6
    • Yu, Y.1    Han, Q.2    Ding, X.3
  • 3
    • 84950251959 scopus 로고    scopus 로고
    • Histogram analysis with automated extraction of brain-tissue region from whole-brain CT images
    • Kondo M, Yamashita K, Yoshiura T, et al. Histogram analysis with automated extraction of brain-tissue region from whole-brain CT images. Springerplus 2015; 4: Article ID: 788.
    • (2015) Springerplus , vol.4
    • Kondo, M.1    Yamashita, K.2    Yoshiura, T.3
  • 4
    • 48949116226 scopus 로고    scopus 로고
    • Cranial CT with 64-, 16-, 4- and single-slice CT systems-comparison of image quality and posterior fossa artifacts in routine brain imaging with standard pro-tocols
    • Ertl-Wagner B, Eftimov L, Blume J, et al. Cranial CT with 64-, 16-, 4- and single-slice CT systems-comparison of image quality and posterior fossa artifacts in routine brain imaging with standard pro-tocols. Eur Radiol 2008; 18(8): 1720-26.
    • (2008) Eur Radiol , vol.18 , Issue.8 , pp. 1720-1726
    • Ertl-Wagner, B.1    Eftimov, L.2    Blume, J.3
  • 5
    • 84937437761 scopus 로고    scopus 로고
    • Pathological brain detection in magnetic resonance imaging scanning by wavelet entropy and hybridization of biogeography-based optimization and particle swarm optimization
    • Zhang Y, Wang S, Dong Z, Phillip P, Ji G, Yang J. Pathological brain detection in magnetic resonance imaging scanning by wavelet entropy and hybridization of biogeography-based optimization and particle swarm optimization. Prog Electromagnet Res 2015; 152: 41-58.
    • (2015) Prog Electromagnet Res , vol.152 , pp. 41-58
    • Zhang, Y.1    Wang, S.2    Dong, Z.3    Phillip, P.4    Ji, G.5    Yang, J.6
  • 6
    • 84928688048 scopus 로고    scopus 로고
    • Automated classification of brain images using wavelet-energy and biogeography-based optimization
    • Yang G, Zhang Y, Yang J, et al. Automated classification of brain images using wavelet-energy and biogeography-based optimization. Multimed Tools Appl 2016; 75: 15601.
    • (2016) Multimed Tools Appl , vol.75 , pp. 15601
    • Yang, G.1    Zhang, Y.2    Yang, J.3
  • 7
    • 84977465820 scopus 로고    scopus 로고
    • Pathological brain detection based on wavelet entropy and Hu moment invariants
    • Zhang Y, Wang S, Sun P, Phillips P. Pathological brain detection based on wavelet entropy and Hu moment invariants. BioMed Mat Eng 2015; 26(s1): 1283-90.
    • (2015) Biomed Mat Eng , vol.26 , Issue.s1 , pp. 1283-1290
    • Zhang, Y.1    Wang, S.2    Sun, P.3    Phillips, P.4
  • 8
    • 84941284847 scopus 로고    scopus 로고
    • A novel method for early diagnosis of Alzheimer's disease based on pseudo Zernike moment from structural MRI
    • Gorji HT, Haddadnia J. A novel method for early diagnosis of Alzheimer's disease based on pseudo Zernike moment from structural MRI. Neuroscience 2015; 305: 361-71.
    • (2015) Neuroscience , vol.305 , pp. 361-371
    • Gorji, H.T.1    Haddadnia, J.2
  • 9
    • 37349003864 scopus 로고    scopus 로고
    • Improving brain tumor characterization on MRI by probabilistic neural networks and non-linear transformation of textural features
    • Georgiadis P, Cavouras D, Kalatzis I, et al. Improving brain tumor characterization on MRI by probabilistic neural networks and non-linear transformation of textural features. Comput Method Program Biomed 2008; 89(1): 24-32.
    • (2008) Comput Method Program Biomed , vol.89 , Issue.1 , pp. 24-32
    • Georgiadis, P.1    Cavouras, D.2    Kalatzis, I.3
  • 10
    • 78651253373 scopus 로고    scopus 로고
    • A novel method for magnetic resonance brain image classification based on adaptive chaotic PSO
    • Wang S, Wu L. A novel method for magnetic resonance brain image classification based on adaptive chaotic PSO. Prog Electromagnet Res 2010; 109: 325-43.
    • (2010) Prog Electromagnet Res , vol.109 , pp. 325-343
    • Wang, S.1    Wu, L.2
  • 11
    • 80053630182 scopus 로고    scopus 로고
    • Comparison of ANFIS and SVM for the classification of brain MRI Pathologies
    • Yonsei University, Seoul, South Korea: IEEE
    • Lahmiri S, Boukadoum M. Comparison of ANFIS and SVM for the classification of brain MRI Pathologies. In: 54th International Midwest Symposium on Circuits and Systems. Yonsei University, Seoul, South Korea: IEEE: 2011. pp. 1-4.
    • (2011) 54Th International Midwest Symposium on Circuits and Systems , pp. 1-4
    • Lahmiri, S.1    Boukadoum, M.2
  • 12
    • 84866525215 scopus 로고    scopus 로고
    • An MR brain images classifier via principal component analysis and kernel support vector machine
    • Wu L. An MR brain images classifier via principal component analysis and kernel support vector machine. Prog Electromagnet Res 2012; 130: 369-88.
    • (2012) Prog Electromagnet Res , vol.130 , pp. 369-388
    • Wu, L.1
  • 13
    • 84884575083 scopus 로고    scopus 로고
    • Classification of MRI brain images using combined wavelet entropy based spider web plots and probabilistic neural network
    • Saritha M, Joseph KP, Mathew AT, et al. Classification of MRI brain images using combined wavelet entropy based spider web plots and probabilistic neural network. Pattern Recogni Lett 2013; 34(16): 2151-56.
    • (2013) Pattern Recogni Lett , vol.34 , Issue.16 , pp. 2151-2156
    • Saritha, M.1    Joseph, K.P.2    Mathew, A.T.3
  • 14
    • 84929627799 scopus 로고    scopus 로고
    • Effect of spider-web-plot in MR brain image classification
    • Dong Z, Ji G. Effect of spider-web-plot in MR brain image classification. Pattern Recogni Lett 2015; 62: 14-16.
    • (2015) Pattern Recogni Lett , vol.62 , pp. 14-16
    • Dong, Z.1    Ji, G.2
  • 15
    • 84899008824 scopus 로고    scopus 로고
    • Computer-aided diagnosis of human brain tumor through MRI: A survey and a new algorithm
    • El-Dahshana E-SA, Mohsen HM, Revett K, Salem A-BM. Computer-aided diagnosis of human brain tumor through MRI: A survey and a new algorithm. Expert Sys Appl 2014; 41(11): 5526-45
    • (2014) Expert Sys Appl , vol.41 , Issue.11 , pp. 5526-5545
    • El-Dahshana, E.-S.1    Mohsen, H.M.2    Revett, K.3    Salem, A.-BM.4
  • 16
    • 84892614873 scopus 로고    scopus 로고
    • Classification of Alzheimer disease based on structural magnetic resonance imaging by kernel support vector machine decision tree
    • Dong Z. Classification of Alzheimer disease based on structural magnetic resonance imaging by kernel support vector machine decision tree. Prog Electromagnet Res 2014; 144: 171-84.
    • (2014) Prog Electromagnet Res , vol.144 , pp. 171-184
    • Dong, Z.1
  • 17
    • 84923171982 scopus 로고    scopus 로고
    • A simple and intelligent approach for brain MRI classification
    • Nazir M, Wahid F, Ali KS. A simple and intelligent approach for brain MRI classification. J Intell Fuzzy Syst 2015; 28(3): 1127-35.
    • (2015) J Intell Fuzzy Syst , vol.28 , Issue.3 , pp. 1127-1135
    • Nazir, M.1    Wahid, F.2    Ali, K.S.3
  • 18
    • 84930681763 scopus 로고    scopus 로고
    • Detection of subjects and brain regions related to Alzheimer's disease using 3D MRI scans based on eigenbrain and machine learning
    • Yuan TF. Detection of subjects and brain regions related to Alzheimer's disease using 3D MRI scans based on eigenbrain and machine learning. Front Comput Neurosci 2015; 9: Article ID: 66.
    • (2015) Front Comput Neurosci , vol.9
    • Yuan, T.F.1
  • 19
    • 84922461060 scopus 로고    scopus 로고
    • Performance analysis of neural networks for classification of medical images with wavelets as a feature extractor
    • Harikumar R, Kumar BV. Performance analysis of neural networks for classification of medical images with wavelets as a feature extractor. Int J Imag Sys Technol 2015; 25(1): 33-40.
    • (2015) Int J Imag Sys Technol , vol.25 , Issue.1 , pp. 33-40
    • Harikumar, R.1    Kumar, B.V.2
  • 20
    • 84937763002 scopus 로고    scopus 로고
    • Classification of mild cognitive impairment and Alzheimer's Disease with machine-learning techniques using H-1 Magnetic Resonance Spectroscopy data
    • Munteanu RC, Fernandez-Lozano C, Abad VM, et al. Classification of mild cognitive impairment and Alzheimer's Disease with machine-learning techniques using H-1 Magnetic Resonance Spectroscopy data. Expert Sys Appli 2015; 42(15-16): 6205-14.
    • (2015) Expert Sys Appli , vol.42 , Issue.15-16 , pp. 6205-6214
    • Munteanu, R.C.1    Fernandez-Lozano, C.2    Abad, V.M.3
  • 21
    • 84945219111 scopus 로고    scopus 로고
    • Full-field hard x-ray microscopy with interdigitated silicon lenses
    • Simons H, Stöhr F, Michael-Lindhard J, et al. Full-field hard x-ray microscopy with interdigitated silicon lenses. Opt Commun 2016; 359: 460-64.
    • (2016) Opt Commun , vol.359 , pp. 460-464
    • Simons, H.1    Stöhr, F.2    Michael-Lindhard, J.3
  • 22
    • 84962650802 scopus 로고    scopus 로고
    • Curve-like structure extraction using minimal path propagation with back-tracing
    • Chen Y, Zhang Y, Yang J, et al. Curve-like structure extraction using minimal path propagation with back-tracing. IEEE T Image Process 2016; 25(2): 988-03.
    • (2016) IEEE T Image Process , vol.25 , Issue.2 , pp. 988-1003
    • Chen, Y.1    Zhang, Y.2    Yang, J.3
  • 23
    • 84945485618 scopus 로고    scopus 로고
    • F-18-Alfatide II PET/CT in healthy human volunteers and patients with brain metastases
    • Yu C, Pan D, Mi B, et al. F-18-Alfatide II PET/CT in healthy human volunteers and patients with brain metastases. Eur J Nucl Med Mol Imaging 2015; 42(13): 2021-28.
    • (2015) Eur J Nucl Med Mol Imaging , vol.42 , Issue.13 , pp. 2021-2028
    • Yu, C.1    Pan, D.2    Mi, B.3
  • 24
    • 84944514570 scopus 로고    scopus 로고
    • Multicenter Semiquantitative Evaluation of I-123-FP-CIT Brain SPECT
    • Skanjeti A, Castellano G, Elia BO, et al. Multicenter Semiquantitative Evaluation of I-123-FP-CIT Brain SPECT. J Neuroimaging 2015; 25(6): 1023-29.
    • (2015) J Neuroimaging , vol.25 , Issue.6 , pp. 1023-1029
    • Skanjeti, A.1    Castellano, G.2    Elia, B.O.3
  • 25
    • 84954184199 scopus 로고    scopus 로고
    • Detection of Alzheimer's Disease by Three-Dimensional Displacement Field Estimation in Structural Magnetic Resonance Imaging
    • Wang S, Zhang Y, Liu G, et al. Detection of Alzheimer's Disease by Three-Dimensional Displacement Field Estimation in Structural Magnetic Resonance Imaging. J Alzheimer's Dis 2016; 50(1): 233-48.
    • (2016) J Alzheimer's Dis , vol.50 , Issue.1 , pp. 233-248
    • Wang, S.1    Zhang, Y.2    Liu, G.3
  • 26
    • 84942368912 scopus 로고    scopus 로고
    • Global linear regression coefficient classifier for recognition
    • Feng Q, Zhu X, Pan J-S. Global linear regression coefficient classifier for recognition. Optik 2015; 126(21): 3234-39.
    • (2015) Optik , vol.126 , Issue.21 , pp. 3234-3239
    • Feng, Q.1    Zhu, X.2    Pan, J.-S.3
  • 27
    • 84876051855 scopus 로고    scopus 로고
    • Linear Regression-based Classifier For Audio Visual Person Identification
    • And Their Applications. Amer University Sharjah, Sharjah, United Arab Emirates: IEEE
    • Alam MR, Togneri R, Sohel F, et al. Linear Regression-based Classifier For Audio Visual Person Identification. In: 1st International Conference on Communications Signal Processing, And Their Applications. Amer University Sharjah, Sharjah, United Arab Emirates: IEEE: 2013. pp. 5.
    • (2013) 1St International Conference on Communications Signal Processing , pp. 5
    • Alam, M.R.1    Togneri, R.2    Sohel, F.3
  • 28
    • 85011032133 scopus 로고    scopus 로고
    • K-fold cross-validation for improving medical classification accuracy and model selection in k-nearest neighbors classifiers
    • Zhao M. K-fold cross-validation for improving medical classification accuracy and model selection in k-nearest neighbors classifiers. Basic Clin Pharmacol Toxicol 2016; 118(S1): 107-07.
    • (2016) Basic Clin Pharmacol Toxicol , vol.118 , Issue.S1 , pp. 107
    • Zhao, M.1
  • 29
    • 84954348805 scopus 로고    scopus 로고
    • An empirical comparison of V-fold penalisation and cross-validation for model selection in distribution-free regression
    • Dhanjal C, Baskiotis N, Clémençon S, Usunier N. An empirical comparison of V-fold penalisation and cross-validation for model selection in distribution-free regression. Patt Anal Appl 2016; 19(1): 41-53.
    • (2016) Patt Anal Appl , vol.19 , Issue.1 , pp. 41-53
    • Dhanjal, C.1    Baskiotis, N.2    Clémençon, S.3    Usunier, N.4
  • 31
    • 84899076098 scopus 로고    scopus 로고
    • An Assessment of Ten-Fold and Monte Carlo Cross Validations for Time Series Forecasting
    • Computing Science And Automatic Control. Mexico City, Mexico: IEEE
    • Fonseca-Delgado R, Gomez-Gil P. An Assessment of Ten-Fold and Monte Carlo Cross Validations for Time Series Forecasting. In: 10th International Conference on Electrical Engineering, Computing Science And Automatic Control. Mexico City, Mexico: IEEE: 2013. pp. 215-220.
    • (2013) 10Th International Conference on Electrical Engineering , pp. 215-220
    • Fonseca-Delgado, R.1    Gomez-Gil, P.2
  • 32
    • 79953158380 scopus 로고    scopus 로고
    • A high speed back propagation neural network for multistage mr brain tumor image segmentation
    • Hemanth DJ, Vijila CKS, Anitha J. A high speed back propagation neural network for multistage mr brain tumor image segmentation. Neural Network World 2011; 21(1): 51-66.
    • (2011) Neural Network World , vol.21 , Issue.1 , pp. 51-66
    • Hemanth, D.J.1    Vijila, C.2    Anitha, J.3
  • 34
    • 84948665356 scopus 로고    scopus 로고
    • NaI(Tl) Detector Efficiency Computation Using Radioactive Parallelepiped Sources Based on Efficiency Transfer Principle
    • Badawi MS, Gouda MM, El-Khatib AM, Thabet AA, Salim AA, Abbas MI. NaI(Tl) Detector Efficiency Computation Using Radioactive Parallelepiped Sources Based on Efficiency Transfer Principle. Sci Technol Nucl Ins 2015; Article ID: 451932.
    • (2015) Sci Technol Nucl Ins
    • Badawi, M.S.1    Gouda, M.M.2    El-Khatib, A.M.3    Thabet, A.A.4    Salim, A.A.5    Abbas, M.I.6
  • 35
    • 84959018146 scopus 로고    scopus 로고
    • Image processing methods to elucidate spatial characteristics of retinal microglia after optic nerve transection
    • Zhang Y, Peng B, Wang S, et al. Image processing methods to elucidate spatial characteristics of retinal microglia after optic nerve transection. Sci Rep 2016; 6: Article ID: 21816.
    • (2016) Sci Rep , vol.6
    • Zhang, Y.1    Peng, B.2    Wang, S.3
  • 36
    • 84959366826 scopus 로고    scopus 로고
    • Three-Dimensional Eigenbrain for the Detection of Subjects and Brain Regions Related with Alzheimer's Disease
    • Zhang Y, Wang S, Phillips P, et al. Three-Dimensional Eigenbrain for the Detection of Subjects and Brain Regions Related with Alzheimer's Disease. J Alzheimers Dis 2016; 50(4): 1163-79.
    • (2016) J Alzheimers Dis , vol.50 , Issue.4 , pp. 1163-1179
    • Zhang, Y.1    Wang, S.2    Phillips, P.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.