Megalopinakophobia: its symptoms and cures

This paper addresses issues in the calculation of a detectability measure for the ideal linear (Hotelling) observer performing a detection task on a digital radiograph. The main computational problem is that the inverse of a very large covariance matrix is required. The conventional approach is to assume some form of stationarity and argue that the matrix is diagonalized by discrete Fourier transformation, but there are many reasons why this assumption is unrealistic. After a brief review of the underlying mathematics, we present several practical algorithms for computing the detectability and some hints as to when each is applicable. The main conclusion is that large matrices should not be feared.

[1]  R. F. Wagner,et al.  Aperture optimization for emission imaging: effect of a spatially varying background. , 1990, Journal of the Optical Society of America. A, Optics and image science.

[2]  H H Barrett,et al.  Effect of random background inhomogeneity on observer detection performance. , 1992, Journal of the Optical Society of America. A, Optics and image science.

[3]  H H Barrett,et al.  Hotelling trace criterion and its correlation with human-observer performance. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[4]  Harrison H. Barrett,et al.  What does DQE say about lesion detectability in digital radiography? , 2001, SPIE Medical Imaging.

[5]  Craig K. Abbey,et al.  Stabilized estimates of Hotelling-observer detection performance in patient-structured noise , 1998, Medical Imaging.

[6]  Harrison H. Barrett,et al.  Hotelling trace criterion as a figure of merit for the optimization of imaging systems , 1986 .

[7]  H H Barrett,et al.  Addition of a channel mechanism to the ideal-observer model. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[8]  H H Barrett,et al.  Objective assessment of image quality: effects of quantum noise and object variability. , 1990, Journal of the Optical Society of America. A, Optics and image science.