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3740 Total Publications

Ensemble learning incorporating uncertain registration.
Simpson, I. J. a, Woolrich, M. W., Andersson, J. L. R., Groves, A. R., & Schnabel, J. a.
2013; Journal IEEE Transactions on Medical Imaging; vol. 32; no. 4; pp. 748-56; doi:10.1109/TMI.2012.2236651
Identification of functional variants from whole-exome sequencing, combined with neuroimaging genetics.
Nho, K., Corneveaux, J. J., Kim, S., Lin, H., Risacher, S. L., Shen, L., … Saykin, A. J.
2013; Journal Molecular Psychiatry; vol. 18; no. 7; pp. 739; doi:10.1038/mp.2013.81
Mapping creatinine- and cystatin C-related white matter brain deficits in the elderly.
Rajagopalan, P., Refsum, H., Hua, X., Toga, A. W., Jack, C. R., Weiner, M. W., & Thompson, P. M.
2013; Journal Neurobiology of Aging; vol. 34; no. 4; pp. 1221-30; doi:10.1016/j.neurobiolaging.2012.10.022
Multiple instance learning for classification of dementia in brain MRI.
Tong, T., Wolz, R., Gao, Q., Hajnal, J. V, & Rueckert, D.
2013; Journal Medical Image Computing and Computer-Assisted Intervention; vol. 16; no. 2; pp. 599-606; doi:10.1007/978-3-642-40763-5_74
Large Deformation Image Classification Using Generalized Locality-Constrained Linear Coding.
Zhang, P., Wee, C., Niethammer, M., & Shen, D.
2013; Journal Medical Image Computing and Computer-Assisted Intervention; pp. 292-299; doi:10.1007/978-3-642-40811-3_37
Segmentation of MR images via discriminative dictionary learning and sparse coding: application to hippocampus labeling.
Tong, T., Wolz, R., Coupé, P., Hajnal, J. V, & Rueckert, D.
2013; Journal Neuroimage; vol. 76; pp. 11-23; doi:10.1016/j.neuroimage.2013.02.069
Modeling the heterogeneity in risk of progression to Alzheimer’s disease across cognitive profiles in mild cognitive impairment.
Tatsuoka, C., Tseng, H., Jaeger, J., Varadi, F., Smith, M. A., Yamada, T., … Lerner, A. J.
2013; Journal Alzheimer's Research and Therapy; vol. 5; no. 2; pp. 14; doi:10.1186/alzrt168
Locally linear embedding (LLE) for MRI based Alzheimer’s disease classification.
Liu, X., Tosun, D., Weiner, M. W., & Schuff, N.
2013; Journal Neuroimage; vol. 83; pp. 148-57; doi:10.1016/j.neuroimage.2013.06.033
Predicting brain activity using a Bayesian spatial model.
Derado, G., Bowman, F. D., & Zhang, L.
2013; Journal Statistical Methods in Medical Research; vol. 22; no. 4; pp. 382-97; doi:10.1177/0962280212448972