Individual subject classification for Alzheimer's disease based on incremental learning using a spatial frequency representation of cortical thickness data.

Cho, Y., Seong, J.K., Jeong, Y., Shin, S.Y., Alzheimer's Disease Neuroimaging Initiative and Whitcher, B. 2012. Individual subject classification for Alzheimer's disease based on incremental learning using a spatial frequency representation of cortical thickness data. NeuroImage. 59 (3), pp. 2217-2230. https://doi.org/10.1016/j.neuroimage.2011.09.085

TitleIndividual subject classification for Alzheimer's disease based on incremental learning using a spatial frequency representation of cortical thickness data.
TypeJournal article
AuthorsCho, Y., Seong, J.K., Jeong, Y., Shin, S.Y., Alzheimer's Disease Neuroimaging Initiative and Whitcher, B.
Abstract

Patterns of brain atrophy measured by magnetic resonance structural imaging have been utilized as significant biomarkers for diagnosis of Alzheimer's disease (AD). However, brain atrophy is variable across patients and is non-specific for AD in general. Thus, automatic methods for AD classification require a large number of structural data due to complex and variable patterns of brain atrophy. In this paper, we propose an incremental method for AD classification using cortical thickness data. We represent the cortical thickness data of a subject in terms of their spatial frequency components, employing the manifold harmonic transform. The basis functions for this transform are obtained from the eigenfunctions of the Laplace–Beltrami operator, which are dependent only on the geometry of a cortical surface but not on the cortical thickness defined on it. This facilitates individual subject classification based on incremental learning. In general, methods based on region-wise features poorly reflect the detailed spatial variation of cortical thickness, and those based on vertex-wise features are sensitive to noise. Adopting a vertex-wise cortical thickness representation, our method can still achieve robustness to noise by filtering out high frequency components of the cortical thickness data while reflecting their spatial variation. This compromise leads to high accuracy in AD classification. We utilized MR volumes provided by Alzheimer's Disease Neuroimaging Initiative (ADNI) to validate the performance of the method. Our method discriminated AD patients from Healthy Control (HC) subjects with 82% sensitivity and 93% specificity. It also discriminated Mild Cognitive Impairment (MCI) patients, who converted to AD within 18 months, from non-converted MCI subjects with 63% sensitivity and 76% specificity. Moreover, it showed that the entorhinal cortex was the most discriminative region for classification, which is consistent with previous pathological findings. In comparison with other classification methods, our method demonstrated high classification performance in both categories, which supports the discriminative power of our method in both AD diagnosis and AD prediction.

JournalNeuroImage
Journal citation59 (3), pp. 2217-2230
ISSN1053-8119
Year2012
PublisherElsevier
Digital Object Identifier (DOI)https://doi.org/10.1016/j.neuroimage.2011.09.085
PubMed ID22008371
Publication dates
Published01 Feb 2012

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Gençay, R., Gradojevic, N., Selçuk, F. and Whitcher, B. 2010. Asymmetry of information flow between volatilities across time scales. Quantitative Finance. 10 (8), pp. 895-915. https://doi.org/10.1080/14697680903460143

A Multi-Center Randomized Proof-of-Concept Clinical Trial Applying [18F]FDG-PET for Evaluation of Metabolic Therapy with Rosiglitazone XR in Mild to Moderate Alzheimer's Disease
Tzimopoulou, S., Cunningham, V.J., Nichols, T.E., Searle, G., Bird, N.P., Mistry, P., Dixon, I.J., Hallett, W.A., Whitcher, B., Brown, A.P., Zvartau-Hind, M., Lotay, N., Lai, R.Y.K., Castiglia, M., Jeter, B., Matthews, J.C., Chen, K., Bandy, D., Reiman, E.M., Gold, M., Rabiner, E.A. and Matthews, P.M. 2010. A Multi-Center Randomized Proof-of-Concept Clinical Trial Applying [18F]FDG-PET for Evaluation of Metabolic Therapy with Rosiglitazone XR in Mild to Moderate Alzheimer's Disease. Journal of Alzheimer's Disease. 22 (4), pp. 1241-1256. https://doi.org/10.3233/jad-2010-100939

Longitudinal changes in white matter disease and cognition in the first year of the Alzheimer disease neuroimaging initiative.
Carmichael, O., Schwarz, C., Drucker, D., Fletcher, E., Harvey, D., Beckett, L., Jack, C.R., Weiner, M., DeCarli, C., Alzheimer's Disease Neuroimaging Initiative and Whitcher, B. 2010. Longitudinal changes in white matter disease and cognition in the first year of the Alzheimer disease neuroimaging initiative. Archives of Neurology. 67 (11), pp. 1370-1378. https://doi.org/10.1001/archneurol.2010.284

Quantitative analysis of dynamic contrast-enhanced MR images based on bayesian P-splines
Schmid, V.J., Whitcher, B., Padhani, A.R. and Yang, G.-Z. 2009. Quantitative analysis of dynamic contrast-enhanced MR images based on bayesian P-splines. IEEE Transactions on Medical Imaging. 28 (6), pp. 789-798. https://doi.org/10.1109/tmi.2008.2007326

Quantifying spatial heterogeneity in dynamic contrast-enhanced MRI parameter maps
Rose, C.J., Mills, S.J., O'Connor, J.P.B., Buonaccorsi, G.A., Roberts, C., Watson, Y., Cheung, S., Zhao, S., Whitcher, B., Jackson, A. and Parker, G.J.M. 2009. Quantifying spatial heterogeneity in dynamic contrast-enhanced MRI parameter maps. Magnetic Resonance in Medicine. 62 (2), pp. 488-499. https://doi.org/10.1002/mrm.22003

A bayesian hierarchical model for the analysis of a longitudinal dynamic contrast-enhanced MRI oncology study
Schmid, V.J., Whitcher, B., Padhani, A.R., Jane Taylor, N. and Yang, G.-Z. 2009. A bayesian hierarchical model for the analysis of a longitudinal dynamic contrast-enhanced MRI oncology study. Magnetic Resonance in Medicine. 61 (1), pp. 163-174. https://doi.org/10.1002/mrm.21807

Anatomically-distinct genetic associations of APOE e{open}4 allele load with regional cortical atrophy in Alzheimer's disease
Filippini, N., Rao, A., Wetten, S., Gibson, R.A., Borrie, M., Guzman, D., Kertesz, A., Loy-English, I., Williams, J., Nichols, T., Whitcher, B. and Matthews, P.M. 2009. Anatomically-distinct genetic associations of APOE e{open}4 allele load with regional cortical atrophy in Alzheimer's disease. NeuroImage. 44 (3), pp. 724-728. https://doi.org/10.1016/j.neuroimage.2008.10.003

Variational Bayesian inference for a nonlinear forward model
Chappell, M.A., Groves, A.R., Whitcher, B. and Woolrich, M.W. 2009. Variational Bayesian inference for a nonlinear forward model. IEEE Transactions on Signal Processing. 57 (1), pp. 223-236. https://doi.org/10.1109/tsp.2008.2005752

Reproducibility of fMRI in the clinical setting: Implications for trial designs
Bosnell, R., Wegner, C., Kincses, Z.T., Korteweg, T., Agosta, F., Ciccarelli, O., De Stefano, N., Gass, A., Hirsch, J., Johansen-Berg, H., Kappos, L., Barkhof, F., Mancini, L., Manfredonia, F., Marino, S., Miller, D.H., Montalban, X., Palace, J., Rocca, M., Enzinger, C., Ropele, S., Rovira, A., Smith, S., Thompson, A., Thornton, J., Yousry, T., Whitcher, B., Filippi, M. and Matthews, P.M. 2008. Reproducibility of fMRI in the clinical setting: Implications for trial designs. NeuroImage. 42 (2), pp. 603-610. https://doi.org/10.1016/j.neuroimage.2008.05.005

A statistical framework to characterise microstructure in high angular resolution diffusion imaging
Olhede, S. and Whitcher, B. 2008. A statistical framework to characterise microstructure in high angular resolution diffusion imaging. 2008 5th IEEE international symposium on biomedical imaging: From nano to macro. Paris, France 14 - 17 May 2008 IEEE . https://doi.org/10.1109/isbi.2008.4541142

A multi-resolution census algorithm for calculating vortex statistics in turbulent flows
Whitcher, B., Lee, T.C.M., Weiss, J.B., Hoar, T.J. and Nychka, D.W. 2008. A multi-resolution census algorithm for calculating vortex statistics in turbulent flows. Journal of the Royal Statistical Society: Series C (Applied Statistics). 57 (3), pp. 293-312. https://doi.org/10.1111/j.1467-9876.2007.00614.x

Using the wild bootstrap to quantify uncertainty in diffusion tensor imaging
Whitcher, B., Tuch, D.S., Wisco, J.J., Sorensen, A.G. and Wang, L. 2007. Using the wild bootstrap to quantify uncertainty in diffusion tensor imaging. Human Brain Mapping. 29 (3), pp. 346-362. https://doi.org/10.1002/hbm.20395

Statistical group comparison of diffusion tensors via multivariate hypothesis testing
Whitcher, B., Wisco, J.J., Hadjikhani, N. and Tuch, D.S. 2007. Statistical group comparison of diffusion tensors via multivariate hypothesis testing. Magnetic Resonance in Medicine. 57 (6), pp. 1065-1074. https://doi.org/10.1002/mrm.21229

Study-level wavelet cluster analysis and data-driven signal models in pharmacological MRI
Schwarz, A.J., Whitcher, B., Gozzi, A., Reese, T. and Bifone, A. 2007. Study-level wavelet cluster analysis and data-driven signal models in pharmacological MRI. Journal of Neuroscience Methods. 159 (2), pp. 346-360. https://doi.org/10.1016/j.jneumeth.2006.07.017

Resampling methods for improved wavelet-based multiple hypothesis testing of parametric maps in functional MRI
Şendur, L., Suckling, J., Whitcher, B. and Bullmore, E. 2007. Resampling methods for improved wavelet-based multiple hypothesis testing of parametric maps in functional MRI. NeuroImage. 37 (4), pp. 1186-1194. https://doi.org/10.1016/j.neuroimage.2007.05.057

Quantifying heterogeneity in dynamic contrast-enhanced MRI parameter maps
Rose, C.J., Mills, S., O'Connor, J.P.B., Buonaccorsi, G.A., Roberts, C., Watson, Y., Whitcher, B., Jayson, G., Jackson, A. and Parker, G.J.M. 2007. Quantifying heterogeneity in dynamic contrast-enhanced MRI parameter maps. MICCAI 2007: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007. Brisbane, Australia 29 Oct - 02 Nov 2007 Springer. https://doi.org/10.1007/978-3-540-75759-7_46

Wavelet-based bootstrapping of spatial patterns on a finite lattice
Whitcher, B. 2006. Wavelet-based bootstrapping of spatial patterns on a finite lattice. Computational Statistics & Data Analysis. 50 (9), pp. 2399-2421. https://doi.org/10.1016/j.csda.2004.12.016

Noninvasive brain imaging for experimental medicine in drug discovery and development: Promise and pitfalls
Whitcher, B. and Matthews, P.M. 2006. Noninvasive brain imaging for experimental medicine in drug discovery and development: Promise and pitfalls. International Journal of Pharmaceutical Medicine. 20, pp. 167-175. https://doi.org/10.2165/00124363-200620030-00003

Semi-parametric analysis of dynamic contrast-enhanced MRI using bayesian P-splines
Schmid, V.J., Whitcher, B. and Yang, G.-Z. 2006. Semi-parametric analysis of dynamic contrast-enhanced MRI using bayesian P-splines. MICCAI 2006: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006. Copenhagen, Denmark 01 - 06 Oct 2006 Springer. https://doi.org/10.1007/11866565_83

Bayesian methods for pharmacokinetic models in dynamic contrast-enhanced magnetic resonance imaging
Schmid, V.J., Whitcher, B., Padhani, A.R., Taylor, N.J. and Yang, G.-Z. 2006. Bayesian methods for pharmacokinetic models in dynamic contrast-enhanced magnetic resonance imaging. IEEE Transactions on Medical Imaging. 25 (12), pp. 1627-1636. https://doi.org/10.1109/tmi.2006.884210

A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs
Achard, S., Salvador, R., Whitcher, B., Suckling, J. and Bullmore, E. 2006. A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs. Journal of Neuroscience. 26 (1), pp. 63-72. https://doi.org/10.1523/jneurosci.3874-05.2006

Co-deposition of salmeterol and fluticasone propionate by a combination inhaler
Theophilus, A., Moore, A., Prime, D., Rossomanno, S., Whitcher, B. and Chrystyn, H. 2006. Co-deposition of salmeterol and fluticasone propionate by a combination inhaler. International Journal of Pharmaceutics. 313 (1-2), pp. 14-22. https://doi.org/10.1016/j.ijpharm.2006.01.018

Time-varying spectral analysis in neurophysiological time series using Hilbert wavelet pairs
Whitcher, Brandon, Craigmile, Peter F. and Brown, Peter 2005. Time-varying spectral analysis in neurophysiological time series using Hilbert wavelet pairs. Signal Processing. 85 (11), pp. 2065-2081. https://doi.org/10.1016/j.sigpro.2005.07.002

Wavelet-based cluster analysis: Data-driven grouping of voxel time courses with application to perfusion-weighted and pharmacological MRI of the rat brain
Whitcher, B., Schwarz, A.J., Barjat, H., Smart, S.C., Grundy, R.I. and James, M.F. 2005. Wavelet-based cluster analysis: Data-driven grouping of voxel time courses with application to perfusion-weighted and pharmacological MRI of the rat brain. NeuroImage. 24 (2), pp. 281-295. https://doi.org/10.1016/j.neuroimage.2004.08.022

Multiple hypothesis mapping of functional MRI data in orthogonal and complex wavelet domains
Şendur, L., Maxim, V., Whitcher, B. and Bullmore, E. 2005. Multiple hypothesis mapping of functional MRI data in orthogonal and complex wavelet domains. IEEE Transactions on Signal Processing. 53 (9), pp. 3413-3426. https://doi.org/10.1109/tsp.2005.853098

Multiscale systematic risk
Gençay, R., Selçuk, F. and Whitcher, B. 2005. Multiscale systematic risk. Journal of International Money and Finance. 24 (1), pp. 55-70. https://doi.org/10.1016/j.jimonfin.2004.10.003

Statistical analysis of pharmacokinetic models in dynamic contrast-enhanced magnetic resonance imaging.
Schmid, V.J., Whitcher, B.J., Yang, G.Z., Taylor, N.J., Padhani, A.R. and Whitcher, B. 2005. Statistical analysis of pharmacokinetic models in dynamic contrast-enhanced magnetic resonance imaging. MICCAI 2005: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005. Palm Springs, CA, USA 26 - 29 Oct 2005 Springer. https://doi.org/10.1007/11566489_109

Wavelet-based estimation for seasonal long-memory processes
Whitcher, B. 2004. Wavelet-based estimation for seasonal long-memory processes. Technometrics. 46 (2), pp. 225-238. https://doi.org/10.1198/004017004000000275

Wavelets and functional magnetic resonance imaging of the human brain
Bullmore, E., Fadili, J., Maxim, V., Şendur, L., Whitcher, Brandon, Suckling, J., Brammer, M. and Breakspear, M. 2004. Wavelets and functional magnetic resonance imaging of the human brain. NeuroImage. 23 (1), pp. S234-S249. https://doi.org/10.1016/j.neuroimage.2004.07.012

Identifying and tracking turbulence structures
Storlie, C., Davis, C., Hoar, T., Lee, T., Nychka, D., Weiss, J.B. and Whitcher, Brandon 2004. Identifying and tracking turbulence structures. 38th Asilomar Conference on Signals, Systems and Computers. California, USA 07-10 IEEE . https://doi.org/10.1109/ACSSC.2004.1399449

Systematic risk and timescales
Gençay, R., Selçuk, F. and Whitcher, B. 2003. Systematic risk and timescales. Quantitative Finance. 3 (2), pp. 108-116. https://doi.org/10.1088/1469-7688/3/2/305

A wavelet solution to the spurious regression of fractionally differenced processes
Fan, Y. and Whitcher, B. 2003. A wavelet solution to the spurious regression of fractionally differenced processes. Applied Stochastic Models in Business and Industry. 19 (3). https://doi.org/10.1002/asmb.497

Stochastic Multiresolution Models for Turbulence
Whitcher, Brandon, Weiss, J.B., Nychka, D.W. and Hoar, T.J. 2003. Stochastic Multiresolution Models for Turbulence. in: Recent Advances and Trends in Nonparametric Statistics Elsevier. pp. 497-509

Testing for homogeneity of variance in time series: Long memory, wavelets, and the Nile River
Whitcher, Brandon, Byers, S.D., Guttorp, P. and Percival, D.B. 2002. Testing for homogeneity of variance in time series: Long memory, wavelets, and the Nile River. Water Resources Research. 38 (5), pp. 12-1 - 12-16. https://doi.org/10.1029/2001wr000509

Scaling properties of foreign exchange volatility
Gençay, R., Selçuk, F. and Whitcher, Brandon 2001. Scaling properties of foreign exchange volatility. Physica A: Statistical Mechanics and its Applications. 289 (1-2), pp. 249-266. https://doi.org/10.1016/s0378-4371(00)00456-8

Simulating gaussian stationary processes with unbounded spectra
Whitcher, B. 2001. Simulating gaussian stationary processes with unbounded spectra. Journal of Computational and Graphical Statistics. 10 (1), pp. 112-134. https://doi.org/10.1198/10618600152418674

Differentiating intraday seasonalities through wavelet multi-scaling
Gençay, R., Selçuk, F. and Whitcher, B. 2001. Differentiating intraday seasonalities through wavelet multi-scaling. Physica A: Statistical Mechanics and its Applications. 289 (3-4), pp. 543-556. https://doi.org/10.1016/s0378-4371(00)00463-5

Wavelet estimation of a local long memory parameter
Whitcher, B. and Jensen, M.J. 2000. Wavelet estimation of a local long memory parameter. Exploration Geophysics. 31 (1-2), pp. 94-103. https://doi.org/10.1071/eg00094

Wavelet analysis of covariance with application to atmospheric time series
Whitcher, Brandon, Guttorp, P. and Percival, D.B. 2000. Wavelet analysis of covariance with application to atmospheric time series. Journal of Geophysical Research Atmospheres. 105 (D11), pp. 14941-14962 2000JD900110. https://doi.org/10.1029/2000JD900110

Multiscale detection and location of multiple variance changes in the presence of long memory
Whitcher, Brandon, Guttorp, P. and Percival, D.B. 2000. Multiscale detection and location of multiple variance changes in the presence of long memory. Journal of Statistical Computation and Simulation. 68 (1), pp. 65-87. https://doi.org/10.1080/00949650008812056

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