Investigation of basic imaging properties in digital radiography. 13. Effect of simple structured noise on the detectability of simulated stenotic lesions

Abstract

We investigated the effects of structured background noise on the detectability of stenotic lesions. Digital subtraction angiographic (DSA) images of stenotic blood vessels were simulated and superimposed onto uniform noise samples. Eighteen-alternative forced choice (18-AFC) experiments were employed to determine the detectability of the stenotic lesion in the structured-noise background of a blood vessel. In this study, the dependence of detectability on lesion size, vessel size, and incident x-ray exposure was examined. Our results indicate that the presence of structured noise in an image will reduce the detectability of a lesion. However, the relative performance of an observer when the lesion size and incident exposure were varied was the same with and without the presence of the structured background. Thus, conclusions obtained previously with regard to changes in the detectability of a lesion in the presence of uniform background noise can be applied directly to conditions in which simple structured anatomic background is present.

An adaptive reference/test paradigm: Application to pulsed fluoroscopy perception

“…In our experiments, the value of u depends upon independent variables such as object size and pulsed acquisition rate. Ohara et al (1989) derived the probability of detection for an M-AFC experiment, and their result is reproduced Figure 2. In this 9-alternative-forced-choice phantom, a disk of 16 pixels in diameter is randomly placed at the center of one of the squares.…”

“…One can derive the probability of a correct choice, p(d') in an M-alternative, forced choice (M-AFC) experiment (Equation A15, in of Ohara et al, 1989), and the result is…”

“…where u, a variable name following the convention of Ohara et al (1989), is the detectability parameter to be estimated. For fixed object contrast and dose, it becomes easier to discriminate between object and no-object as u, and hence d', increases.…”

“…To analyze experiments, we use a popular signal detection model (Burgess, 1995;Elliott, 1964), and we closely follow the derivation given by Ohara et al (1989). The model hypothesizes that visual sensory inputs are converted to a single, continuous decision variable internal to the observer, with Gaussian probability density functions for the cases "object present" and "no object present."…”

Contrast, noise, and blur affect performance and appreciation of digital radiographs

“…A similar observation was made earlier. 22 A final remark about the appropriateness of the model for these detection results concerns the fact that the results were obtained with frozen noise, meaning that a single noise pattern was used for every scene and noise level. Thus, the visibility of details at a given noise level could be influenced by the actual instance of the stochastic noise process.…”