Evaluating the predictive power of multivariate tensor-based morphometry in Alzheimer's disease progression via convex fused sparse group Lasso

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 9034, Issue , 2014, Pages

  Tsao, Sinchai ^a   Gajawelli, Niharika ^b   Zhou, Jiayu ^c   Shi, Jie ^c   Ye, Jieping ^c   Wang, Yalin ^c   Lepore, Natasha ^b  

^a UNIVERSITY OF WASHINGTON   (United States)

^b CHILDREN S HOSPITAL LOS ANGELES   (United States)

^c ARIZONA STATE UNIVERSITY   (United States)

Author keywords

ADAS Cog; Alzheimers Disease; Disease Progression; Feature Selection; Fused Lasso; Hippocampus; Multi task learning; Tensor based Morphometry

Indexed keywords

ARTIFICIAL INTELLIGENCE; FEATURE EXTRACTION; FORECASTING; IMAGE PROCESSING; NEURODEGENERATIVE DISEASES; NEUROIMAGING; SURFACE ANALYSIS; TENSORS;

ADAS-COG; ALZHEIMERS DISEASE; DISEASE PROGRESSION; FUSED LASSOS; HIPPOCAMPUS; MULTITASK LEARNING; TENSOR-BASED MORPHOMETRY;

BRAIN;

EID: 84902095854     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.2042720     Document Type: Conference Paper

References (11)

1. Zhou, J., Liu, J., Narayan, V. A., and Ye, J., "Modeling Disease Progression via Multi-task Learning," NeuroImage (2013).
2. Shi, J., Thompson, P. M., Gutman, B., andWang, Y., "Surface uid registration of conformal representation: Application to detect disease burden and genetic inuence on hippocampus," NeuroImage (2013).
3. Caselli, R. J., Locke, D. E. C., Dueck, A. C., Knopman, D. S., Woodru-, B. K., Ho-man-Snyder, C., Rademakers, R., Fleisher, A. S., and Reiman, E. M., "The neuropsychology of normal aging and preclinical alzheimer's disease," Alzheimers Dement (Mar 2013).
4. Elias-Sonnenschein, L. S., Helisalmi, S., Natunen, T., Hall, A., Paajanen, T., Herukka, S.-K., Laitinen, M., Remes, A. M., Koivisto, A. M., Mattila, K. M., Lehtimaki, T., Verhey, F. R. J., Visser, P. J., Soininen, H., and Hiltunen, M., "Genetic loci associated with alzheimer's disease and cerebrospinal uid biomarkers in afinnish case-control cohort," PLoS One 8(4), e59676 (2013).
5. Teipel, S. J., Grothe, M., Lista, S., Toschi, N., Garaci, F. G., and Hampel, H., "Relevance of magnetic resonance imaging for early detection and diagnosis of alzheimer disease," Med Clin North Am 97, 399{424 (May 2013).
6. Becker, G. A., Ichise, M., Barthel, H., Luthardt, J., Patt, M., Seese, A., Schultze-Mosgau, M., Rohde, B., Gertz, H.-J., Reininger, C., and Sabri, O., "Pet quantification of 18f-orbetaben binding to-amyloid deposits in human brains," J Nucl Med (Mar 2013).
7. Blennow, K. and Zetterberg, H., "The application of cerebrospinal uid biomarkers in early diagnosis of alzheimer disease," Med Clin North Am 97, 369{76 (May 2013).
8. Hajjar, I., Brown, L., Mack, W. J., and Chui, H., "Alzheimer pathology and angiotension receptor blockers," JAMA Neurol 70, 414 (Mar 2013).
9. Mueller, S. G., Weiner, M. W., Thal, L. J., Petersen, R. C., Jack, C. R., Jagust, W., Trojanowski, J. Q., Toga, A. W., and Beckett, L., "Ways toward an early diagnosis in alzheimer's disease: the alzheimer's disease neuroimaging initiative (adni)," Alzheimers Dement 1, 55{66 (Jul 2005).
10. Wang, Y., Yuan, L., Shi, J., Greve, A., Ye, J., Toga, A. W., Reiss, A. L., and Thompson, P. M., "Applying tensor-based morphometry to parametric surfaces can improve mri-based disease diagnosis," Neuroimage 74, 209{30 (Jul 2013).
11. Jenkinson, M., Beckmann, C. F., Behrens, T. E. J., Woolrich, M. W., and Smith, S. M., "Fsl," Neuroim-age 62, 782{90 (Aug 2012).