Effects of hardware heterogeneity on the performance of SVM Alzheimer's disease classifier, Neuroimage, vol.58, pp.785-792, 2011. ,
Different multivariate techniques for automated classification of MRI data in Alzheimer's disease and mild cognitive impairment, Psychiatry Res, vol.212, pp.89-98, 2013. ,
The diagnosis of mild cognitive impairment due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease, Alzheimers Dement, vol.7, pp.270-279, 2011. ,
, Alzheimer's & Dementia: The Journal of the Alzheimer's Association, vol.12, pp.645-653, 2016.
,
Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls, Neuroimage, vol.145, pp.137-165, 2017. ,
,
A fast diffeomorphic image registration algorithm, Neuroimage, vol.38, pp.95-113, 2007. ,
Unified segmentation, Neuroimage, vol.26, pp.839-851, 2005. ,
DOI : 10.1016/j.neuroimage.2005.02.018
An efficient 3D deep convolutional network for Alzheimer's disease diagnosis using MR images, Presented at the 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), pp.149-153, 2018. ,
Probability distribution function-based classification of structural MRI for the detection of Alzheimer's disease, Comput. Biol. Med, vol.64, pp.208-216, 2015. ,
No Unbiased Estimator of the Variance of K-Fold Cross-Validation, J. Mach. Learn. Res, vol.5, pp.1089-1105, 2004. ,
Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge, NeuroImage, vol.111, pp.562-579, 2015. ,
URL : https://hal.archives-ouvertes.fr/hal-01220123
Predicting conversion from MCI to AD with FDG-PET brain images at different prodromal stages, Comput. Biol. Med, vol.58, pp.101-109, 2015. ,
Does feature selection improve classification accuracy? Impact of sample size and feature selection on classification using anatomical magnetic resonance images, Neuroimage, vol.60, pp.59-70, 2012. ,
Scoring by nonlocal image patch estimator for early detection of Alzheimer's disease, NeuroImage: Clinical, vol.1, pp.141-152, 2012. ,
Combined evaluation of FDG-PET and MRI improves detection and differentiation of dementia, PLoS ONE, vol.6, 2011. ,
The Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging: methodology and baseline characteristics of 1112 individuals recruited for a longitudinal study of Alzheimer's disease, International Psychogeriatrics, vol.21, pp.672-687, 2009. ,
Addressing population aging and Alzheimer's disease through the Australian Imaging Biomarkers and Lifestyle study: Collaboration with the Alzheimer's Disease Neuroimaging Initiative, Alzheimer's & Dementia, vol.6, pp.291-296, 2010. ,
Prediction of Alzheimer's disease in subjects with mild cognitive impairment from the ADNI cohort using patterns of cortical thinning, Neuroimage, vol.65, pp.511-521, 2013. ,
Neuroimaging markers for the prediction and early diagnosis of Alzheimer's disease dementia, Trends in Neurosciences, vol.34, pp.430-442, 2011. ,
Multivariate Data Analysis and Machine Learning in Alzheimer's Disease with a Focus on Structural Magnetic Resonance Imaging, Journal of Alzheimer's Disease, vol.41, pp.685-708, 2014. ,
Spatial patterns of brain atrophy in MCI patients, identified via high-dimensional pattern classification, predict subsequent cognitive decline, NeuroImage, vol.39, pp.1731-1743, 2008. ,
FreeSurfer, Neuroimage, vol.62, pp.774-781, 2012. ,
Estimating the age of healthy subjects from T1-weighted MRI scans using kernel methods: exploring the influence of various parameters, Neuroimage, vol.50, pp.883-892, 2010. ,
,
Spatial registration and normalization of images, Human Brain Mapping, vol.3, pp.165-189, 1995. ,
,
Comparison of feature representations in MRI-based MCI-to-AD conversion prediction, Magn Reson Imaging, vol.50, pp.84-95, 2018. ,
Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in python, Front Neuroinform, vol.5, 2011. ,
The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments, 2016. ,
URL : https://hal.archives-ouvertes.fr/inserm-01345616
Automatic segmentation of brain MRIs of 2-year-olds into 83 regions of interest, Neuroimage, vol.40, pp.672-684, 2008. ,
Random forest-based similarity measures for multi-modal classification of Alzheimer's disease, NeuroImage, vol.65, pp.167-175, 2013. ,
DOI : 10.1016/j.neuroimage.2012.09.065
URL : http://europepmc.org/articles/pmc3516432?pdf=render
,
Manifold population modeling as a neuro-imaging biomarker: Application to ADNI and ADNI-GO, NeuroImage, vol.94, pp.275-286, 2014. ,
,
Principles of Classification Analyses in Mild Cognitive Impairment (MCI) and Alzheimer Disease, Journal of Alzheimer's Disease, vol.26, pp.389-394, 2011. ,
Three-dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe, Hum Brain Mapp, vol.19, pp.224-247, 2003. ,
Spatially augmented LPboosting for AD classification with evaluations on the ADNI dataset, Neuroimage, vol.48, pp.138-149, 2009. ,
Enhancement of MR images using registration for signal averaging, J Comput Assist Tomogr, vol.22, pp.324-333, 1998. ,
Introduction to the recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease, Alzheimers Dement, vol.7, pp.257-262, 2011. ,
Update on the Magnetic Resonance Imaging core of the Alzheimer's Disease Neuroimaging Initiative, Alzheimer's & Dementia, vol.6, pp.212-220, 2010. ,
The Alzheimer's disease neuroimaging initiative (ADNI): MRI methods, J. Magn. Reson. Imaging, vol.27, pp.685-691, 2008. ,
,
Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade, Lancet Neurol, vol.9, pp.70299-70305, 2010. ,
The Alzheimer's Disease Neuroimaging Initiative positron emission tomography core, Alzheimer's & Dementia, vol.6, pp.221-229, 2010. ,
The Alzheimer's Disease Neuroimaging Initiative 2 PET Core, Alzheimer's & Dementia, vol.11, pp.757-771, 2015. ,
Manifold regularized multitask feature learning for multimodality disease classification, Hum. Brain Mapp, vol.36, pp.489-507, 2015. ,
AICHA: An atlas of intrinsic connectivity of homotopic areas, J. Neurosci. Methods, vol.254, pp.46-59, 2015. ,
URL : https://hal.archives-ouvertes.fr/hal-01197121
, Workshop of the International Conference on Machine Learning
Automatic classification of MR scans in Alzheimer's disease, Brain, vol.131, pp.681-689, 2008. ,
Practice parameter: diagnosis of dementia (an evidence-based review), Report of the Quality Standards Subcommittee of the American Academy of Neurology, vol.56, pp.1143-1153, 2001. ,
Amyloid-? Imaging with Pittsburgh Compound B and Florbetapir: Comparing Radiotracers and Quantification Methods, J Nucl Med, vol.54, pp.70-77, 2013. ,
The first step for neuroimaging data analysis: DICOM to NIfTI conversion, J. Neurosci. Methods, vol.264, pp.47-56, 2016. ,
,
Ensemble sparse classification of Alzheimer's disease, NeuroImage, vol.60, pp.1106-1116, 2012. ,
View-centralized multiatlas classification for Alzheimer's disease diagnosis, Hum Brain Mapp, vol.36, pp.1847-1865, 2015. ,
Landmark-based deep multi-instance learning for brain disease diagnosis, Med Image Anal, vol.43, pp.157-168, 2018. ,
Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer's Disease using structural MR and FDG-PET images, Sci Rep, vol.8, 2018. ,
DTI measurements for Alzheimer's classification, Phys. Med. Biol, vol.62, p.2361, 2017. ,
Open Access Series of Imaging Studies (OASIS): Cross-sectional MRI Data in Young, Middle Aged, Nondemented, and Demented Older Adults, Journal of Cognitive Neuroscience, vol.19, pp.1498-1507, 2007. ,
,
Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease, Neurology, vol.34, pp.939-944, 1984. ,
The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease, Alzheimers Dement, vol.7, pp.263-269, 2011. ,
,
Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects, Neuroimage, vol.104, pp.398-412, 2015. ,
Inference for the Generalization Error, Machine Learning, vol.52, pp.239-281, 2003. ,
A comparison of three brain atlases for MCI prediction, J. Neurosci. Methods, vol.221, pp.139-150, 2014. ,
Effects of imaging modalities, brain atlases and feature selection on prediction of Alzheimer's disease, J. Neurosci. Methods, vol.256, pp.168-183, 2015. ,
Scikit-learn: Machine Learning in Python, Journal of Machine Learning Research, vol.12, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00650905
Alzheimer's Disease Neuroimaging Initiative (ADNI): clinical characterization, Neurology, vol.74, pp.201-209, 2010. ,
,
Scanning the horizon: towards transparent and reproducible neuroimaging research, Nat. Rev. Neurosci, vol.18, pp.115-126, 2017. ,
URL : https://hal.archives-ouvertes.fr/cea-01896468
Early diagnosis of Alzheimer's disease using cortical thickness: impact of cognitive reserve, Brain, vol.132, pp.2036-2047, 2009. ,
,
Neuropredict: Easy Machine Learning And Standardized Predictive Analysis Of Biomarkers, 2017. ,
Impact of spatial scale and edge weight on predictive power of cortical thickness networks, 2017. ,
A review on neuroimagingbased classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages, NeuroImage, vol.155, pp.530-548, 2017. ,
Clinica: an open source software platform for reproducible clinical neuroscience studies, Presented at the Annual meeting of the Organization for Human Brain Mapping-OHBM, 2018. ,
URL : https://hal.archives-ouvertes.fr/hal-01760658
Clinical Prediction from Structural Brain MRI Scans: A Large-Scale Empirical Study, Neuroinform, vol.13, pp.31-46, 2015. ,
Magnetic resonance imaging biomarkers for the early diagnosis of Alzheimer's disease: a machine learning approach, Front. Neurosci, vol.9, 2015. ,
Alzheimer's Disease Neuroimaging Initiative, 2016. A large-scale comparison of cortical thickness and volume methods for measuring Alzheimer's disease severity, Neuroimage Clin, vol.11, pp.802-812 ,
Construction of a 3D probabilistic atlas of human cortical structures, Neuroimage, vol.39, pp.1064-1080, 2008. ,
Ensemble support vector machine classification of dementia using structural MRI and mini-mental state examination, J. Neurosci. Methods, vol.302, pp.66-74, 2018. ,
Toward defining the preclinical stages of Alzheimer's disease: recommendations from the National Institute on AgingAlzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease, Alzheimers Dement, vol.7, pp.280-292, 2011. ,
Deep ensemble learning of sparse regression models for brain disease diagnosis, Med Image Anal, vol.37, pp.101-113, 2017. ,
The relative importance of imaging markers for the prediction of Alzheimer's disease dementia in mild cognitive impairment-Beyond classical regression, NeuroImage: Clinical, vol.8, pp.583-593, 2015. ,
PETPVC: a toolbox for performing partial volume correction techniques in positron emission tomography, Phys Med Biol, vol.61, pp.7975-7993, 2016. ,
The importance of appropriate partial volume correction for PET quantification in Alzheimer's disease, Eur. J. Nucl. Med. Mol. Imaging, vol.38, pp.1104-1119, 2011. ,
Comparison of Feature Selection Techniques in Machine Learning for Anatomical Brain MRI in Dementia, Neuroinformatics, vol.14, pp.279-296, 2016. ,
Multiple instance learning for classification of dementia in brain MRI, Medical Image Analysis, vol.18, pp.808-818, 2014. ,
Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain, Neuroimage, vol.15, pp.273-289, 2002. ,
,
Assessing and tuning brain decoders: Cross-validation, caveats, and guidelines, Neuroimage, vol.145, pp.166-179, 2017. ,
URL : https://hal.archives-ouvertes.fr/hal-01332785
Alzheimer's disease diagnosis in individual subjects using structural MR images: validation studies, Neuroimage, vol.39, pp.1186-1197, 2008. ,
Alzheimer's Disease Neuroimaging Initiative, 2014. The effects of intracranial volume adjustment approaches on multiple regional MRI volumes in healthy aging and Alzheimer's disease, Front Aging Neurosci, vol.6 ,
Regional magnetic resonance imaging measures for multivariate analysis in Alzheimer's disease and mild cognitive impairment, Brain Topogr, vol.26, pp.9-23, 2013. ,
Mild cognitive impairment-beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment, J. Intern. Med, vol.256, pp.240-246, 2004. ,
Multi-method analysis of MRI images in early diagnostics of Alzheimer's disease, PLoS ONE, vol.6, 2011. ,
Accurate multimodal probabilistic prediction of conversion to Alzheimer's disease in patients with mild cognitive impairment, NeuroImage: Clinical, vol.2, pp.735-745, 2013. ,
Multimodal Discrimination of Alzheimer's Disease Based on Regional Cortical Atrophy and Hypometabolism, PLOS ONE, vol.10, 2015. ,
Multimodal classification of Alzheimer's disease and mild cognitive impairment, NeuroImage, vol.55, pp.856-867, 2011. ,
,
A novel matrix-similarity based loss function for joint regression and classification in AD diagnosis, Neuroimage, vol.100, pp.91-105, 2014. ,