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Publications

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2110 Total Publications

Unsupervised segmentation, clustering, and groupwise registration of heterogeneous populations of brain MR images
Ribbens, A., Hermans, J., Maes, F., Vandermeulen, D., & Suetens, P.
PMID: 23797244 ; 2014; Journal IEEE Transactions on Medical Imaging; vol. 33; no. 2; pp. 201-24; doi:10.1109/TMI.2013.2270114

A Robust Deep Model for Improved Classification of AD/MCI Patients
Li, F., Tran, L., Thung, K.-H., Ji, S., Shen, D., & Li, J.
PMID: 25955998 ; PMCID:4573581 ; 2014; Journal Machine Learning in Medical Imaging; vol. 8679; pp. 240-247; doi:10.1007/978-3-319-10581-9_30

Hierarchical Interactions Model for Predicting Mild Cognitive Impairment (MCI) to Alzheimer’s Disease (AD) Conversion
Li, H., Liu, Y., Gong, P., Zhang, C., & Ye, J.
PMID: 24416143 ; PMCID:3885394 ; 2014; Journal PloS One; vol. 9; no. 1; pp. e82450; doi:10.1371/journal.pone.0082450

Longitudinal Effects of Metabolic Syndrome on Alzheimer and Vascular Related Brain Pathology
Lin, F., Lo, R. Y., Cole, D., Ducharme, S., Chen, D.-G., Mapstone, M., & Porsteinsson, A.
PMID: 25337075 ; 2014; Journal Dementia and Geriatric Cognitive Disorders Extra; vol. 4; no. 2; pp. 184-94; doi:10.1159/000363285

Hierarchical Fusion of Features and Classifier Decisions for Alzheimer’s Disease Diagnosis
Liu, M., Zhang, D., & Shen, D.
PMID: 23417832 ; PMCID:4132886 ; 2014; Journal Human Brain Mapping; vol. 35; no. 4; pp. 1305-19; doi:10.1002/hbm.22254

Disentangling normal aging from Alzheimer's disease in structural magnetic resonance images
Lorenzi M1, Pennec X2, Frisoni GB3, Ayache N2; Alzheimer's Disease Neuroimaging Initiative
PMID: 25311276 ; 2014; Journal Neurobiology of Aging; vol. 36; pp. S42-52; doi:10.1016/j.neurobiolaging.2014.07.046

Operationalizing hippocampal volume as an enrichment biomarker for amnestic MCI trials: effect of algorithm, test-retest variability and cut-point on trial cost, duration and sample size
Yu, P., Sun, J., Wolz, R., Stephenson, D., Brewer, J., Fox, N. C., … Schwarz, A. J.
PMID: 24211008 ; PMCID:4201941 ; 2014; Journal Neurobiology of Aging; vol. 35; pp. 808-818; doi:10.1016/j.neurobiolaging.2013.09.039

Alzheimer'sdisease Neuroimaging Initiative1. Amygdalar atrophy in early Alzheimer's disease.
Klein-Koerkamp Y, Heckemann RA, Ramdeen KT, Moreaud O, Keignart S, Krainik A, Hammers A, Baciu M, Hot P;
2014; Journal Current Alzheimer's Research; vol. 11; no. 3; pp. 239-52;

Integration and relative value of biomarkers for prediction of MCI to AD progression: Spatial patterns of brain atrophy, cognitive scores, APOE genotype and CSF biomarkers.
Da, X., Toledo, J. B., Zee, J., Wolk, D. a., Xie, S. X., Ou, Y., … Davatzikos, C.
2014; Journal Neuroimage: Clinical; vol. 4; pp. 164-173; doi:10.1016/j.nicl.2013.11.010

Genetic variation modifies risk for neurodegeneration based on biomarker status.
Hohman, T. J., Koran, M. E. I., & Thornton-Wells, T. A
2014; Journal Frontiers in Aging Neuroscience; vol. 6; pp. 183; doi:10.3389/fnagi.2014.00183