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Publications

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1739 Total Publications

Latent feature representation with stacked auto-encoder for AD/MCI diagnosis.
Suk, H.-I., Lee, S.-W., & Shen, D.
2013; Journal Brain Structure and Function; pp. 1-19; doi:10.1007/s00429-013-0687-3

White matter hyperintensities and amyloid are independently associated with entorhinal cortex volume among individuals with mild cognitive impairment.
Guzman, V. a., Carmichael, O. T., Schwarz, C., Tosto, G., Zimmerman, M. E., & Brickman, A. M.
2013; Journal Alzheimer's and Dementia; vol. 9; no. 5; pp. S124-S131; doi:10.1016/j.jalz.2012.11.009

Regional magnetic resonance imaging measures for multivariate analysis in Alzheimer’s disease and mild cognitive impairment.
Westman, E., Aguilar, C., Muehlboeck, J.-S., & Simmons, A.
2013; Journal Brain Topography; vol. 26; no. 1; pp. 9-23; doi:10.1007/s10548-012-0246-x

Heart-type fatty acid binding protein and vascular endothelial growth factor: cerebrospinal fluid biomarker candidates for Alzheimer’s disease.
Guo, L.-H., Alexopoulos, P., & Perneczky, R.
2013; Journal European Archives of Psychiatry and Clinical Neuroscience; vol. 263; no. 7; pp. 553-60; doi:10.1007/s00406-013-0405-4

Biomarker-based prediction of progression in MCI: Comparison of AD signature and hippocampal volume with spinal fluid amyloid-β and tau.
Dickerson, B. C., & Wolk, D. A.
2013; Journal Frontiers in Aging Neuroscience; vol. 5; pp. 55; doi:10.3389/fnagi.2013.00055

Dynamics of brain structure and cognitive function in the Alzheimer’s disease neuroimaging initiative.
Song, X., Mitnitski, A., Zhang, N., Chen, W., & Rockwood, K.
2013; Journal Journal of Neurology, Neurosurgery, and Psychiatry; vol. 84; no. 1; pp. 71-8; doi:10.1136/jnnp-2012-303579

Amyloid-β imaging with Pittsburgh compound B and florbetapir: comparing radiotracers and quantification methods.
Landau, S. M., Breault, C., Joshi, A. D., Pontecorvo, M., Mathis, C. a, Jagust, W. J., & Mintun, M. a.
2013; Journal Journal of Nuclear Medicine; vol. 54; no. 1; pp. 70-7; doi:10.2967/jnumed.112.109009

Genetic interactions associated with 12-mo atrophy in hippocampus and entorhinal cortex in ADNI
Meda, S. A., Koran, M. E. I., Pryweller, J. R., Vega, J. N., & Thornton-Wells, T. A.
PMID: 23107432 ; PMCID:3570748 ; 2013; Journal Neurobiology of Aging; vol. 34; no. 5; pp. 1518.e9-18; doi:10.1016/j.neurobiolaging.2012.09.020

Mapping Dynamic Changes in Ventricular Volume onto Baseline Cortical Surfaces in Normal Aging, MCI, and Alzheimer’s Disease*
Madsen, S. K., Gutman, B. A., Joshi, S. H., Toga, A. W., Jack, C. R., Weiner, M. W., & Thompson, P. M.
PMID: 25152934 ; PMCID:4138607 ; 2013; Journal Multimodal Brain Image Analysis; vol. 8159; pp. 84-94; doi:10.1007/978-3-319-02126-3_9

How early can we predict Alzheimer’s disease using computational anatomy?
Adaszewski, S., Dukart, J., Kherif, F., Frackowiak, R., & Draganski, B.
PMID: 23890839 ; 2013; Journal Neurobiology of Aging; vol. 34; no. 12; pp. 2815-2826; doi:10.1016/j.neurobiolaging.2013.06.015