Huang, C., Liang, S., Niethammer, M., Zhu, H.T. (2015). Disease Region Detection of Longitudinal Knee MRI data. IEEE Transaction on Medical Imaging, 34, 1914-1927. Winner of Best Paper award in ASA SI Session, 2014.

An H, Ford AL, Chen Y, Zhu H, Ponisio R, Kumar G, Modir-Shanechi A, Khoury N, Vo KD, Williams JA, Derdeyn CP, Diringer MN, Panagos P, Powers WJ, Lee JM, Lin W. Defining the Ischemic Penumbra using Magnetic Resonance Oxygen Metabolic Index. Stroke, in press, 2015.

S.J. Lee, R. J. Steiner, S. Luo, M. C. Neale, M. Styner, H. Zhu, J.H. Gilmore. (2015). Quantitative tract-based white matter heritability in twin neonates. NeuroImage, 111, 123–135.

Lu, Z. H., Zhu, H.T., R.C. Knickmeyer, P.F. Sullivan, W.N. Stephanie, and Fei Zou, Multiple SNP-sets Analysis for Genome-wide Association Studies through Bayesian Latent Variable Selection. Genetic Epidemiology, 39, 664-677, 2015.

D. Kong, K. S. Giovanello, Y.L. Wang, W. Lin, E. Lee, Y. Fan, P. M. Doraiswamy, and Hongtu Zhu, ADNI (2015). Predicting Alzheimer’s disease using combined imaging-whole genome SNP data. Journal of Alzheimer’s Disease, 46: 695-702.

M.Huang, T.Nichols, C.Huang, Y.Yang, Z. Lu, Q. Feng, R.C. Knickmeyer, H.Zhu, and for ADNI. (2015). FVGWAS: Fast Voxelwise Genome Wide Association Analysis of Large-scale Imaging Genetic Data. NeuroImage, 118, 613-627.

Lee, E.J., Zhu, H.T., D. Kong, and Ibrahim, J. G. A Bayesian functional linear Cox regression model (BFLCRM) for predicting time to conversion to Alzheimer's disease. Annals of Applied Statistics, 9, 2153-2178, 2015.

Rao, S., Ibrahim, J. G., Cheng, G. Yap, P.T., and Zhu, H.T. SR-HARDI: Spatially regularizing high angular resolution diffusion imaging. Journal of Computational and Graphical Statistics, in press, 2015.

Lu, Z.H., Chow, S. M., Sherwood, A. and Zhu, H.T. Bayesian analysis of nonlinear latent stochastic differential equations with application to human dynamics. Annals of Applied Statistics, 9, 1601-1620, 2015.

Zhu, H, Chen, M.H., and Ibrahim, J.G. Diagnostic measures for the Cox regression model with missing covariates, Biometrika, 102, 907-923, 2015.

Huang, C., Styner, M., and Zhu, H.T. Penalized mixtures of offset-normal shape factor analyzers with application in clustering high-dimensional shape data. Journal of American Statistical Association, 110, 946-961, 2015.

Mihye, A., Shen, H.P., Lin, W. L., and Zhu, H.T. A sparse reduced rank framework for group analysis of functional neuroimaging data. Statistica Sinica, 25, 295-312, 2015.

Gao, Q. B., Mihye, A., and Zhu, H.T. Cook’s distance measures for varying coefficient models with functional response. Technometrics, 57, 268-280, 2015.

Guo, R.X., Ahn Mihye, and Zhu, HT. Spatially weighted principal component analysis for imaging classification, Journal of Computational and Graphical Statistics, 24(1), 274-296, 2015.

Sun, Q., Zhu, H.T., Liu, Y. F., and Ibrahim, J.G. SPReM: Sparse Projection regression model for high-dimensional linear regression. Journal of American Statistical Association, 110, 289-302, 2015.