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2.
Automatic ROI selection in structural brain MRI using SOM 3D projection.
by Ortiz, Andrés
PloS one, 2014, Vol.9(4), p.e93851

3.
aBEAT: a toolbox for consistent analysis of longitudinal adult brain MRI.
by Dai, Yakang
PloS one, 2013, Vol.8(4), p.e60344

4.
Mapping the genetic variation of regional brain volumes as explained by all common SNPs from the ADNI study.
by Bryant, Christopher
PloS one, 2013, Vol.8(8), p.e71723

5.
A FDG-PET Study of Metabolic Networks in Apolipoprotein E ε4 Allele Carriers.
by Yao, Zhijun
PloS one, 2015, Vol.10(7), p.e0132300

6.
Effects of baseline CSF α-synuclein on regional brain atrophy rates in healthy elders, mild cognitive impairment and Alzheimer's disease.
by Mattsson, Niklas
PloS one, 2013, Vol.8(12), p.e85443

7.
Estimating long-term multivariate progression from short-term data.
by Donohue, Michael C
Alzheimer's & dementia : the journal of the Alzheimer's Association, October 2014, Vol.10(5 Suppl), pp.S400-S410

8.
Basal forebrain degeneration precedes and predicts the cortical spread of Alzheimer's pathology
by Schmitz, Taylor W.
Schmitz, T. W., R. Nathan Spreng, M. W. Weiner, P. Aisen, R. Petersen, C. R. Jack, W. Jagust, et al. 2016. “Basal forebrain degeneration precedes and predicts the cortical spread of Alzheimer's pathology.” Nature Communications 7 (1): 13249. doi:10.1038/ncomms13249. http://dx.doi.org/10.1038/ncomms13249.

9.
Cerebrospinal fluid markers including trefoil factor 3 are associated with neurodegeneration in amyloid-positive individuals.
by Paterson, R W
Translational psychiatry, July 29, 2014, Vol.4, p.e419

10.
Association of brain amyloid-β with cerebral perfusion and structure in Alzheimer's disease and mild cognitive impairment.
by Mattsson, Niklas
Brain : a journal of neurology, May 2014, Vol.137, pp.1550-1561

11.
Subjective cognitive complaints contribute to misdiagnosis of mild cognitive impairment.
by Edmonds, Emily C
Journal of the International Neuropsychological Society : JINS, September 2014, Vol.20(8), pp.836-847

12.
Rich club analysis in the Alzheimer's disease connectome reveals a relatively undisturbed structural core network.
by Daianu, Madelaine
Human brain mapping, August 2015, Vol.36(8), pp.3087-3103

13.
Estimating anatomical trajectories with Bayesian mixed-effects modeling.
by Ziegler, G
NeuroImage, November 1, 2015, Vol.121, pp.51-68

14.
Improved inference in Bayesian segmentation using Monte Carlo sampling: application to hippocampal subfield volumetry.
by Iglesias, Juan Eugenio
Medical image analysis, October 2013, Vol.17(7), pp.766-778

15.
Tau and Amyloid-β Cerebrospinal Fluid Biomarkers have Differential Relationships with Cognition in Mild Cognitive Impairment.
by Malpas, Charles B
Journal of Alzheimer's disease : JAD, 2015, Vol.47(4), pp.965-975

16.
Cerebral Microbleeds, CSF p-Tau, and Cognitive Decline: Significance of Anatomic Distribution.
by Chiang, G C
AJNR. American journal of neuroradiology, September 2015, Vol.36(9), pp.1635-1641

17.
Association of Cerebrospinal Fluid Neurofilament Light Concentration With Alzheimer Disease Progression.
by Zetterberg, Henrik
JAMA neurology, January 2016, Vol.73(1), pp.60-67

18.
The future is now: model-based clinical trial design for Alzheimer's disease.
by Romero, K
Clinical pharmacology and therapeutics, March 2015, Vol.97(3), pp.210-214

19.
Reference tissue normalization in longitudinal (18)F-florbetapir positron emission tomography of late mild cognitive impairment.
by Shokouhi, Sepideh
Alzheimer's research & therapy, January 15, 2016, Vol.8, p.2

20.
Altered effective connectivity patterns of the default mode network in Alzheimer's disease: an fMRI study.
by Zhong, Yufang
Neuroscience letters, August 22, 2014, Vol.578, pp.171-175
