Camouflaged deconvolution with application to blood curve modeling in fdg pet studies

Journal of the American Statistical Association

Volumn 92, Issue 440, 1997, Pages 1293-1303

  Olshen, Adam B ^a,b   O'sullivan, Finbarr ^b  

^a STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b UNIVERSITY OF WASHINGTON   (United States)

Author keywords

Cross validation; Kinetic analysis; Positron emission tomography; Regularization

Indexed keywords

EID: 0031319973     PISSN: 01621459     EISSN: 1537274X     Source Type: Journal    
DOI: 10.1080/01621459.1997.10473650     Document Type: Article

References (30)

1. Breiman, L., Friedman, J. H., Olshen, R. A., and Stone, C. J.(1984), Classification and Regression Trees, Belmont, CA: Wadsworth.
2. Carroll, R. J., and Hall, P.(1988), "Optimal Rates of Convergence for Deconvolving a Density,"Journal of the American Statistical Association,83, 1184-1186.
3. Cox, D. D., and O'Sullivan, F.(1990), "Asymptotic Analysis of Penalized Likelihood and Related Estimators,"The Annals of Statistics, 18, 1676-1695.
4. Davidian, M., and Giltinan, D. M.(1995), Nonlinear Models for Repeated Measurement Data, London: Chapman and Hall.
5. Efron, B., and Tibshirani, R.(1993), An introduction to the Bootstrap, New York: Chapman and Hall.
6. Hastie, T., and Tibshirani, R.(1990), Generalized Additive Models, New York: Chapman and Hall.
7. Mendelsohn, J., and Rice, J.(1982), "Deconvolution of Microftuorometric Histograms With B-Splines,"Journal of the American Statistical Association,77, 748-753.
8. Nychka, D., and Cox, D. D.(1989), "Convergence Rates for Regularized Solutions of Integral Equations From Discrete Noisy Data,"The Annals of Statistics, 17, 556-572.
9. Nychka, D., Wahba, G., Goldfarb, S., and Pugh, T.(1984), "CrossValidated Spline Methods for the Estimation of Tumor Size Distributions From Observations on Two-Dimensional Cross-Sections,"Journal of the American Statistical Association, 79, 832-846.
10. Olshen, A. B.(1997), "Modeling PET Blood Curves," unpublished Ph.D. dissertation, University of Washington, Dept. of Biostatistics.
11. Ortega, J. M.(1988), "Efficient Implementations of Certain Iterative Methods,"SiAM Journal of Scientific and Statistical Computing, 9, 882-891.
12. O'Sullivan, F.(1990), "Convergence Characteristics of Methods of Regularization Estimates for Non-Linear Operator Equations,"SiAM Journal on Numerical Analysis, 27, 1635-1649.
13. O'Sullivan, F. (1993), "Discretized Laplacian Smoothing by Fourier Methods,"Journal of the American Statistical Association, 86, 634-642.
14. O'Sullivan, F. (1994), "Metabolic Images From Dynamic Positron Emission Tomography Studies,"Statistical Methods in Medical Research, 3, 87-101.
15. O'Sullivan, F., and O'Sullivan, J.(1988), "Deconvolution of Episodic Hormone Data: An Analysis of the Role of Season on the Onset of Puberty in Bovine Females,"Biometrics, 44, 339-353.
16. O'Sullivan, F., and Wahba, G.(1985), "A Cross-Validated Bayesian Retrieval Algorithm for Non-Linear Remote Sensing Experiments,"Journal of Computational Physics, 59, 441-445.
17. Phelps, M. E., Huang, S. c, Hoffman, E. J., Selin, C., Sokoloff, L., and Kuhl, D. E.(1979), "Tomographic Measurement of Local Cerebral Glucose Metabolic Rate in Humans With [F-18]2-Fluoro-2-Deoxy-DGlucose: Validation of Method,"The Annals of Neurology, 6, 371-388.
18. Priestly, M. B. 1980, Spectral Analysis and Time Series, London: Academic Press.
19. Rice, J. A.(1986), "Choice of Smoothing Parameter in Deconvolution Problems,"Contemporary Mathematics, 59, 137-151.
20. Rice, J. A., and Silverman, B.W. 1990, "Estimating the Mean and Covariance Structure Nonparametrically When the Data are Curves," Journal of the Royal Statistical Society, Ser B, 53, 233-243.
21. Rosenblatt, M., and Lii, K.(1982), "Non-Gaussian Linear Processes, Phase and Deconvolution,"The Annals of Statistics, 10, 1195-1208.
22. Schulz, T. J.(1993), "Multiframe Blind Deconvolution of Astronomical Images,"Journal of the Optical Society of America, 10, 1064-1073.
23. Stockham, T. G., Cannon, T. M., and Ingebretsen, R. B.(1975), "Blind Deconvolution Through Digital Signal Processing,"Proceedings of the IEEE, 63, 678-692.
24. Stone, C. J. (1982), "Optimal Global Rates of Convergence for Nonparametric Regression," The Annals of Statistics, 10, 1040-1053.
25. Takikawa, S., Dhawan, V., Spetsieris, P., Robeson, w., Chaly, T., Dahl, R., Margouleff, D., and Eidelberg, D. (1993), "Noninvasive Quantitative Fluorodeoxyglucose PET Studies With an Estimated Input Function Derived From a Population-Based Arterial Blood Curve,"Radiology, 188,131-136.
26. Tekalp, A. M., Kaufman, H., and Woods, J. W.(1986), "Identification of Image and Blur Parameters for the Restoration of Noncausal Blurs,"IEEE Transactions on Acoustics, Speech, and Signal Processing, 34,963-972.
27. Vardi, Y., Shepp, L. A., and Kaufman, L.(1985), "A Statistical Model for Positron Emission Tomography,"The Journal of the American Statistical Association, 80, 8-20.
28. Wahba, G.(1990), Spline Models in Statistics, Philadelphia: SIAM.
29. Wahba, G., and Wang, Y.(1990), "When is the Optimal Regularization Parameter Insensitive to the Choice of the Loss Function,"Communication in Statistics, 19, 1685-1700.
30. Wilson, C. B. 1.H. (1992), "PET Scanning in Oncology,"European Journal of Cancer, 28, 508-510.