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Volumn 35, Issue 4, 2014, Pages 1305-1319

Hierarchical fusion of features and classifier decisions for Alzheimer's disease diagnosis

Author keywords

Alzheimer's disease; Brain disease diagnosis; Hierarchical classification; Local patch; Mild cognitive impairment (MCI); SVM classifier

Indexed keywords

AGED; ALZHEIMER DISEASE; ARTICLE; BRAIN REGION; CLASSIFICATION ALGORITHM; CLASSIFIER; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; DISEASE CLASSIFICATION; FEMALE; GRAY MATTER; HUMAN; MAJOR CLINICAL STUDY; MALE; MILD COGNITIVE IMPAIRMENT; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; PRIORITY JOURNAL; PROBLEM SOLVING; ALGORITHM; ARTIFICIAL INTELLIGENCE; BRAIN; COMPUTER ASSISTED DIAGNOSIS; DIFFERENTIAL DIAGNOSIS; FACTUAL DATABASE; NONMYELINATED NERVE; PATHOLOGY; PROCEDURES; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; VALIDATION STUDY;

EID: 84896396327     PISSN: 10659471     EISSN: 10970193     Source Type: Journal    
DOI: 10.1002/hbm.22254     Document Type: Article
Times cited : (114)

References (40)
  • 2
    • 10444221886 scopus 로고    scopus 로고
    • Diversity creation methods: A survey and categorisation
    • Brown G, Wyatt J, Harris R, Yao X (2005): Diversity creation methods: A survey and categorisation. Information Fusion 6:5-20.
    • (2005) Information Fusion , vol.6 , pp. 5-20
    • Brown, G.1    Wyatt, J.2    Harris, R.3    Yao, X.4
  • 3
    • 0036161011 scopus 로고    scopus 로고
    • Choosing multiple parameters for support vector machines
    • Chapelle O, Vapnik V, Bousquet O, Mukherjee S (2002): Choosing multiple parameters for support vector machines. Mach Learn 46:131-159.
    • (2002) Mach Learn , vol.46 , pp. 131-159
    • Chapelle, O.1    Vapnik, V.2    Bousquet, O.3    Mukherjee, S.4
  • 4
    • 84862776712 scopus 로고    scopus 로고
    • Does feature selection improve classification accuracy? Impact of sample size and feature selection on classification using anatomical magnetic resonance images
    • for the Alzheimer's Disease Neuroimaging Initiative.
    • Chu C, Hsu A-L, Chou K-H, Bandettini P, Lin C, for the Alzheimer's Disease Neuroimaging Initiative (2012): Does feature selection improve classification accuracy? Impact of sample size and feature selection on classification using anatomical magnetic resonance images. Neuroimage 60:59-70.
    • (2012) Neuroimage , vol.60 , pp. 59-70
    • Chu, C.1    Hsu, A.-L.2    Chou, K.-H.3    Bandettini, P.4    Lin, C.5
  • 5
    • 79955059574 scopus 로고    scopus 로고
    • Automatic classification of patients with Alzheimer's disease from structural MRI: a comparison of ten methods using the ADNI database
    • Cuingnet R, Gerardin E, Tessieras J, Auzias G, Lehericy S, Habert MO, Chupin M, Benali H, Colliot O (2011): Automatic classification of patients with Alzheimer's disease from structural MRI: a comparison of ten methods using the ADNI database. Neuroimage 56:766-781.
    • (2011) Neuroimage , vol.56 , pp. 766-781
    • Cuingnet, R.1    Gerardin, E.2    Tessieras, J.3    Auzias, G.4    Lehericy, S.5    Habert, M.O.6    Chupin, M.7    Benali, H.8    Colliot, O.9
  • 7
    • 39749189507 scopus 로고    scopus 로고
    • Detection of prodromal Alzheimer's disease via pattern classification of magnetic resonance imaging
    • Davatzikos C, Fan Y, Wu X, Shen D, Resnick SM (2008a): Detection of prodromal Alzheimer's disease via pattern classification of magnetic resonance imaging. Neurobiol Aging 29:514-523.
    • (2008) Neurobiol Aging , vol.29 , pp. 514-523
    • Davatzikos, C.1    Fan, Y.2    Wu, X.3    Shen, D.4    Resnick, S.M.5
  • 8
    • 44649136049 scopus 로고    scopus 로고
    • Individual patient diagnosis of AD and FTD via high-dimensional pattern classification of MRI
    • Davatzikos C, Resnick SM, Wu X, Parmpi P, Clark CM (2008b): Individual patient diagnosis of AD and FTD via high-dimensional pattern classification of MRI. Neuroimage 41:1220-1227.
    • (2008) Neuroimage , vol.41 , pp. 1220-1227
    • Davatzikos, C.1    Resnick, S.M.2    Wu, X.3    Parmpi, P.4    Clark, C.M.5
  • 9
    • 79960624860 scopus 로고    scopus 로고
    • Classification of structural images via high-dimensional image warping, robust feature extraction, and SVM
    • Fan Y, Shen D, Davatzikos C (2005): Classification of structural images via high-dimensional image warping, robust feature extraction, and SVM. Med Image Comput Comput Assist Interv 3749:1-8.
    • (2005) Med Image Comput Comput Assist Interv , vol.3749 , pp. 1-8
    • Fan, Y.1    Shen, D.2    Davatzikos, C.3
  • 10
    • 33846264886 scopus 로고    scopus 로고
    • COMPARE: Classification of morphological patterns using adaptive regional elements
    • Fan Y, Shen D, Gur RC, Gur RE, Davatzikos C (2007): COMPARE: Classification of morphological patterns using adaptive regional elements. IEEE Trans Med Imaging 26:93-105.
    • (2007) IEEE Trans Med Imaging , vol.26 , pp. 93-105
    • Fan, Y.1    Shen, D.2    Gur, R.C.3    Gur, R.E.4    Davatzikos, C.5
  • 11
    • 67949103436 scopus 로고    scopus 로고
    • Spatially augmented LPboosting for AD classification with evaluations on the ADNI dataset
    • Hinrichs C, Singh V, Mukherjee L, Xu G, Chung MK, Johnson SC (2009): Spatially augmented LPboosting for AD classification with evaluations on the ADNI dataset. Neuroimage 48:138-149.
    • (2009) Neuroimage , vol.48 , pp. 138-149
    • Hinrichs, C.1    Singh, V.2    Mukherjee, L.3    Xu, G.4    Chung, M.K.5    Johnson, S.C.6
  • 12
    • 30444438344 scopus 로고    scopus 로고
    • Voxel-based morphometric comparison between early- and late-onset mild Alzheimer's disease and assessment of diagnostic performance of z score images
    • Ishii K, Kawachi T, Sasaki H, Kono AK, Fukuda T, Kojima Y, Mori E (2005): Voxel-based morphometric comparison between early- and late-onset mild Alzheimer's disease and assessment of diagnostic performance of z score images. Am J Neuroradiol 26:333-340.
    • (2005) Am J Neuroradiol , vol.26 , pp. 333-340
    • Ishii, K.1    Kawachi, T.2    Sasaki, H.3    Kono, A.K.4    Fukuda, T.5    Kojima, Y.6    Mori, E.7
  • 18
    • 1642574430 scopus 로고    scopus 로고
    • Morphological classification of brains via high-dimensional shape transformations and machine learning methods
    • Lao Z, Shen D, Xue Z, Karacali B, Resnick SM, Davatzikos C (2004): Morphological classification of brains via high-dimensional shape transformations and machine learning methods. Neuroimage 21:46-57.
    • (2004) Neuroimage , vol.21 , pp. 46-57
    • Lao, Z.1    Shen, D.2    Xue, Z.3    Karacali, B.4    Resnick, S.M.5    Davatzikos, C.6
  • 20
    • 82755161873 scopus 로고    scopus 로고
    • Discriminant analysis of longitudinal cortical thickness changes in Alzheimer's disease using dynamic and network features
    • Li Y, Wang Y, Wu G, Shi F, Zhou L, Lin W, Shen D (2011): Discriminant analysis of longitudinal cortical thickness changes in Alzheimer's disease using dynamic and network features. Neurobiol Aging 33:427.e15-427.e30.
    • (2011) Neurobiol Aging , vol.33 , pp. 15-30
    • Li, Y.1    Wang, Y.2    Wu, G.3    Shi, F.4    Zhou, L.5    Lin, W.6    Shen, D.7
  • 21
    • 84896397650 scopus 로고    scopus 로고
    • Hierarchical ensemble of multi-level classifiers for diagnosis of Alzheimer's disease. In: Proceedings of the Third International Workshop on Machine Learning in Medical Imaging (MLMI), Nice, France, October 1, 2012.
    • Liu M, Zhang D, Yap P-T, Shen D (2012): Hierarchical ensemble of multi-level classifiers for diagnosis of Alzheimer's disease. In: Proceedings of the Third International Workshop on Machine Learning in Medical Imaging (MLMI), Nice, France, October 1, 2012.
    • (2012)
    • Liu, M.1    Zhang, D.2    Yap, P.-T.3    Shen, D.4
  • 24
    • 77950343082 scopus 로고    scopus 로고
    • Use of SVM methods with surface-based cortical and volumetric subcortical measurements to detect Alzheimer's disease
    • Oliveira PJ, Nitrini R, Busatto G, Buchpiguel C, Sato J, Amaro EJ (2010): Use of SVM methods with surface-based cortical and volumetric subcortical measurements to detect Alzheimer's disease. J Alzheimer Dis 19:1263-1272.
    • (2010) J Alzheimer Dis , vol.19 , pp. 1263-1272
    • Oliveira, P.J.1    Nitrini, R.2    Busatto, G.3    Buchpiguel, C.4    Sato, J.5    Amaro, E.J.6
  • 26
    • 10444224737 scopus 로고    scopus 로고
    • Classifier selection for majority voting
    • Ruta D, Gabrys B (2005): Classifier selection for majority voting. Information Fusion, 6:63-81.
    • (2005) Information Fusion , vol.6 , pp. 63-81
    • Ruta, D.1    Gabrys, B.2
  • 27
    • 77957966081 scopus 로고    scopus 로고
    • Feature fusion hierarchies for gender classification. In: The 19th International Conference on Pattern Recognition (ICPR), IEEE, Tampa, Florida,USA. pp.
    • Scalzo F, Bebis G, Nicolescu M, Loss L, Tavakkoli A (2008): Feature fusion hierarchies for gender classification. In: The 19th International Conference on Pattern Recognition (ICPR), IEEE, Tampa, Florida, USA. pp1-4.
    • (2008) , pp. 1-4
    • Scalzo, F.1    Bebis, G.2    Nicolescu, M.3    Loss, L.4    Tavakkoli, A.5
  • 28
    • 34948819674 scopus 로고    scopus 로고
    • Adaptive patch features for object class recognition with learned hierarchical models. IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, Minneapolis, Minnesota, USA.
    • Scalzo F, Piater JH (2007): Adaptive patch features for object class recognition with learned hierarchical models. IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, Minneapolis, Minnesota, USA. pp1-8.
    • (2007) , pp. 1-8
    • Scalzo, F.1    Piater, J.H.2
  • 29
    • 0037229905 scopus 로고    scopus 로고
    • Very high resolution morphometry using mass-preserving deformations and HAMMER elastic registration
    • Shen D, Davatzikos C (2003): Very high resolution morphometry using mass-preserving deformations and HAMMER elastic registration. Neuroimage 18:28-41.
    • (2003) Neuroimage , vol.18 , pp. 28-41
    • Shen, D.1    Davatzikos, C.2
  • 30
    • 40049091999 scopus 로고    scopus 로고
    • Hierarchical fusion of multi-spectral face images for improved recognition performance
    • Singh R, Vatsa M, Noore A (2008): Hierarchical fusion of multi-spectral face images for improved recognition performance. Information Fusion, 9:200-210.
    • (2008) Information Fusion , vol.9 , pp. 200-210
    • Singh, R.1    Vatsa, M.2    Noore, A.3
  • 31
    • 0031987382 scopus 로고    scopus 로고
    • A nonparametric method for automatic correction of intensity nonuniformity in MRI data
    • Sled JG, Zijdenbos AP, Evans AC (1998): A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging 17:87-97.
    • (1998) IEEE Trans Med Imaging , vol.17 , pp. 87-97
    • Sled, J.G.1    Zijdenbos, A.P.2    Evans, A.C.3
  • 32
    • 77949784467 scopus 로고    scopus 로고
    • Sparse multiple kernel learning for signal processing applications
    • Subrahmanya N, Shin YC (2010): Sparse multiple kernel learning for signal processing applications. IEEE Trans Pattern Anal Mach Intell 32:788-798.
    • (2010) IEEE Trans Pattern Anal Mach Intell , vol.32 , pp. 788-798
    • Subrahmanya, N.1    Shin, Y.C.2
  • 33
    • 33644857555 scopus 로고    scopus 로고
    • Neural networks for longitudinal studies in Alzheimer's disease
    • Tandon R, Adak S, Kaye J (2006): Neural networks for longitudinal studies in Alzheimer's disease. Artif Intell Med 36:245-255.
    • (2006) Artif Intell Med , vol.36 , pp. 245-255
    • Tandon, R.1    Adak, S.2    Kaye, J.3
  • 34
    • 77956051102 scopus 로고    scopus 로고
    • Auto-context and its application to high-level vision tasks and 3d brain image segmentation
    • Tu Z, Bai X (2010): Auto-context and its application to high-level vision tasks and 3d brain image segmentation. IEEE Trans Pattern Anal Mach Intell 32:1744-1757.
    • (2010) IEEE Trans Pattern Anal Mach Intell , vol.32 , pp. 1744-1757
    • Tu, Z.1    Bai, X.2
  • 37
    • 33846575157 scopus 로고    scopus 로고
    • Pattern classification using principal components of cortical thickness and its discriminative pattern in schizophrenia
    • Yoon U, Lee JM, Im K, Shin YW, Cho BH, Kim IY, Kwon JS, Kim SI (2007): Pattern classification using principal components of cortical thickness and its discriminative pattern in schizophrenia. Neuroimage 34:1405-1415.
    • (2007) Neuroimage , vol.34 , pp. 1405-1415
    • Yoon, U.1    Lee, J.M.2    Im, K.3    Shin, Y.W.4    Cho, B.H.5    Kim, I.Y.6    Kwon, J.S.7    Kim, S.I.8
  • 38
    • 83055184373 scopus 로고    scopus 로고
    • Multi-modal multi-task learning for joint prediction of multiple regression and classification variables in Alzheimer's disease
    • Zhang D, Shen D (2011): Multi-modal multi-task learning for joint prediction of multiple regression and classification variables in Alzheimer's disease. Neuroimage 59:895-907.
    • (2011) Neuroimage , vol.59 , pp. 895-907
    • Zhang, D.1    Shen, D.2
  • 39
    • 79952073234 scopus 로고    scopus 로고
    • Multimodal classification of Alzheimer's disease and mild cognitive impairment
    • Zhang D, Wang Y, Zhou L, Yuan H, Shen D (2011): Multimodal classification of Alzheimer's disease and mild cognitive impairment. Neuroimage 55:856-867.
    • (2011) Neuroimage , vol.55 , pp. 856-867
    • Zhang, D.1    Wang, Y.2    Zhou, L.3    Yuan, H.4    Shen, D.5
  • 40
    • 79960471063 scopus 로고    scopus 로고
    • Hierarchical anatomical brain networks for MCI prediction: revisiting volumetric measures
    • Zhou L, Wang Y, Li Y, Yap PT, Shen D (2011): Hierarchical anatomical brain networks for MCI prediction: revisiting volumetric measures. Plos One 6:e21935.
    • (2011) Plos One , vol.6
    • Zhou, L.1    Wang, Y.2    Li, Y.3    Yap, P.T.4    Shen, D.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.