Abstract
The use of linear discriminant functions, and particularly a discriminant function derived from the work of Harold Hotelling, as a means of assessing image quality is reviewed. The relevant theory of ideal or Bayesian observers is briefly reviewed, and the circumstances under which this observer reduces to a linear discriminant are discussed. The Hotelling oberver is suggested as a linear discriminant in more general circumstances where the ideal observer is nonlinear and usually very difficult to calculate. Methods of calculation of the Hotelling discriminant and the associated figure of merit, the Hotelling trace, are discussed. Psychophysical studies carried out at the University of Arizona to test the predictive value of the Hotelling observer are reviewed, and it is concluded that the Hotelling model is quite useful as a predictive tool unless there are high-pass noise correlations introduced by post-processing of the images. In that case, we suggest that the Hotelling observer be modified to include spatial-frequency-selective channels analogous to those in the visual system.
Preview
Unable to display preview. Download preview PDF.
References
Barrett HH, Rolland JP, Wagner RF, and Myers KJ (1989). Detection of known signals in inhomogeneous, random backgrounds. Proc. SPIE, 1090:176–182.
Barrett HH (1990). Objective assessment of image quality: effect of object variability and quantum noise, J. Opt. Soc. Am. A. 7:1266–1278.
Cargill EB (1989). A mathematical liver model and its application to system optimization and texture analysis. Ph.D. Dissertation, University of Arizona.
Fiete RD, Barrett HH, Smith WE, and Myers KJ (1987). The Hotelling trace criterion and its correlation with human observer performance. J. Opt. Soc. Am. A. 4:945–953.
Fisher RA (1936). The use of multiple measurements in taxonomic problems. Ann. Eugenics 7 (part2):179–188.
Gooley TA (1990). Quantitative comparisons of statistical methods in image reconstruction. Ph. D. dissertation, University of Arizona.
Hotelling H (1931). The generalization of Student's ratio. Ann. Math. Stat. 2:360–378.
Myers KJ, Barrett HH, Borgstrom MC, Patton DD, and Seeley GW (1985). Effect of noise correlation on detectability of disk signals in medical imaging. J. Opt. Soc. Am. A, 2:1752–1759.
Myers KJ and Barrett HH (1987). Addition of a channel mechanism to the ideal-observer model. J. Opt. Soc. Am. A, 46:2447–2457.
Rolland JPY, (1990). Factors influencing lesion detection in medical imaging. Ph. D. dissertation, University of Arizona.
Smith WE and Barrett HH (1986). Hotelling trace criterion as a figure of merit for the optimization of imaging systems. J. Opt. Soc. Am. A, 3:717–725.
Smith WE and Barrett HH (1988). Linear estimation theory applied to the evaluation of a priori information and system optimization in coded-aperture imaging. J. Opt. Soc. Am. A,5:315–330.
White TA, Barrett HH, Cargill EB, Fiete RD, and Ker M (1989). The use of the Hotelling trace to optimize collimator performance. The Society of Nuclear Medicine 36th Annual Meeting, St. Louis, MO, (abstract).
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1991 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Barrett, H.H., Gooley, T., Girodias, K., Rolland, J., White, T., Yao, J. (1991). Linear discriminants and image quality. In: Colchester, A.C.F., Hawkes, D.J. (eds) Information Processing in Medical Imaging. IPMI 1991. Lecture Notes in Computer Science, vol 511. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0033773
Download citation
DOI: https://doi.org/10.1007/BFb0033773
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-54246-9
Online ISBN: 978-3-540-47521-7
eBook Packages: Springer Book Archive