Joint estimation of multiple clinical variables of neurological diseases from imaging patterns

2010 7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2010 - Proceedings

Volumn , Issue , 2010, Pages 852-855

  Fan, Yong ^a,b   Kaufer, Daniel ^a   Shen, Dinggang ^a  

^a UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

^b INSTITUTE OF AUTOMATION   (China)

Author keywords

ADAS Cog; Alzheimer's disease; Bayesian regression; MMSE; Structural MR brain image

Indexed keywords

ALZHEIMER'S DISEASE; BAYESIAN REGRESSION; BAYESIAN REGRESSION METHOD; BRAIN IMAGES; CONTINUOUS TRANSITIONS; CROSS VALIDATION; FEATURE SELECTION; JOINT ESTIMATION; MORPHOLOGICAL MEASURES; NEUROLOGICAL DISEASE; REGRESSION METHOD; SUPPRESSING NOISE;

BAYESIAN NETWORKS; FEATURE EXTRACTION; MEDICAL IMAGING; PATHOLOGY; REGRESSION ANALYSIS;

DISEASES;

EID: 77955198893     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2010.5490120     Document Type: Conference Paper

References (12)

1. P. Thompson, K. Hayashi, et al., "Tracking Alzheimer's disease," Annals of New York academy of Sciences, vol. 1097, pp. 183-214, 2007.
2. C. Chu, S. Klöppel, et al., "Regression analysis for clinical scores of Alzheimer's Disease using multivariate machine learning method," in Human Brain Mapping Chicago, IL, USA, 2007.
3. S. Duchesne, A. Caroli, et al., "Predicting clinical variable from MRI features: application to MMSE in MCI," in MICCAI, 2005, pp. 392-399.
4. M. E. Tipping, "Sparse Bayesian learning and the relevance vector machine," Journal of Machine Learning Research, vol. 1, pp. 211-244, 2001.
5. J. Ashburner, J. G. Csernansky, et al., "Computer-assisted imaging to assess brain structure in healthy and diseased brains," The Lancet (Neurology), vol. 2, pp. 79-88, 2003.
6. I. Guyon and A. Elisseeff, "An introduction to variable and feature selection," Journal of Machine Learning Research, vol. 3, pp. 1157-1182, 2003.
7. P. Boyle and M. Frean, "Dependent Gaussian processes," in Advances in Neural Information Processing Systems, 2005, pp. 217-224.
8. E. V. Bonilla, K. M. A. Chai, and C. K. I. Williams, "Multitask Gaussian Process Prediction," in Advances in Neural Information Processing Systems 2008.
9. A. Thayananthan, R. Navaratnam, et al., "Pose estimation and tracking using multivariate regression," Pattern Recognition Letters, vol. 29, pp. 1302-1310, 2008.
10. R. M. Neal, Bayesian learning for neural networks: Springer, 1996.
11. I. Guyon, J. Weston, et al., "Gene Selection for Cancer Classification using Support Vector Machines," Machine Learning, vol. 46, pp. 389-422, January 2002.
12. L. Breiman, "Bagging predictors," Machine Learning, vol. 24, pp. 123-140, 1996.