We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)
References
[1]
[1]Aykroyd, R.G. and Green, PJ. (1991). Global and local priors, and the location of lesions using gamma-camera imagery. Philosophical Trans. Roy. Soc. London Ser. A, 337, 323–342.Google Scholar
[2]
[2]Besag, J.E. (1975). Statistical analysis of non lattice data. The statistician24, 179–195.Google Scholar
[3]
[3]Besag, J.E. (1986). On the statistical analysis of dirty pictures. J. R. Statist. Soc. B48, 259–302.Google Scholar
[4]
[4]Cressie, N.A.C. (1993). Statistics for spatial data. Wiley, Chichester.CrossRefGoogle Scholar
[5]
[5]Geman, S. and Geman, D. (1984). Stochastic relaxation, Gibbs distributions, and the bayesian restoration of images. IEEE Trans. PAMI, pp. 721–741.Google Scholar
[6]
[6]Geman, S. and McClure, D.E. (1987). Statistical methods for tomographic image reconstruction. In Proc. 46th Sess. Inst. Stat. Inst. Bulletin ISI52, pp. 5–21.Google Scholar
[7]
[7]Karssemeijer, N. (1992). Application of bayesian methods to segmentation in medical images. In Lecture Notes in Statistics. Stochastic Models, Statistical Methods, and Algorithms in Image Analysis, 74, eds. Barone, P., Frigesi, A. and Piccioni, M.. Springer-Verlag, pp. 203–218.Google Scholar