Observer detection performance loss: target-size uncertainty

The effect of target size and target-size uncertainty on human observers' ability to detect Gaussian and disk targets in spatially uncorrelated and correlated noise was measured. Disk and Gaussian targets were centered in circular areas (diameter, 128 pixels) of uncorrelated noise and uncorrelated noise filtered to resemble CT noise. Size uncertainty was introduced in the target stimuli by presenting targets with effective areas that ranging from 15 to 10,000 pixels. A constant non-prewhitening, matched- filter signal-to-noise ratio (NPW-SNR) was maintained for all target sizes within each trial by adjusting target contrast. Stimulus sets were rendered on the gray-scale monitor of the computer workstation used to collect observer responses. Observers rated for each stimulus the likelihood that a target was present. The observer ratings were analyzed using a multiple-distributing extension of the bi- normal ROC curve fitting procedure. A control experiment evaluated the influence of the circular noise area on performance with size-specified targets. Observer detection performance loss, the ratio of d' to NPW-SNR, decreased for small and large targets. Variations of target shape and noise correlation had no significant effect on performance loss. Observer performance when target was uncertain was the same as observer performance when the target size was specified. In the control trials the investigator specifies the target size to the observer, yet the observer cannot exploit that information. The observer apparently uses same perceptual resources in both the experimental and control trials to render a rating and consequently performs similarly in size-uncertain and size-specified trials. These results suggest a substantial role of higher order mechanisms in the detection of compact targets in noisy backgrounds.

[1]  P R Moran A physical statistics theory for detectability of target signals in noisy images. I. Mathematical background, empirical review, and development of theory. , 1982, Medical physics.

[2]  P F Judy,et al.  Evaluation of video gray-scale display. , 1992, Medical physics.

[3]  R. F. Wagner,et al.  Unified SNR analysis of medical imaging systems , 1985, Physics in medicine and biology.

[4]  Philip F. Judy,et al.  Observer detection efficiency with target size uncertainty , 1995, Medical Imaging.

[5]  R G Swensson,et al.  Display thresholding of images and observer detection performance. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[6]  R. Swensson,et al.  Analysis of rating data from multiple-alternative tasks☆ , 1989 .

[7]  R. F. Wagner,et al.  Efficiency of human visual signal discrimination. , 1981, Science.

[8]  D. Dorfman,et al.  Maximum-likelihood estimation of parameters of signal-detection theory and determination of confidence intervals—Rating-method data , 1969 .

[9]  D G Pelli,et al.  Uncertainty explains many aspects of visual contrast detection and discrimination. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[10]  P F Judy,et al.  Detection of noisy visual targets: Models for the effects of spatial uncertainty and signal-to-noise ratio , 1981, Perception & psychophysics.

[11]  Philip F. Judy,et al.  Detectability Of Lesions Of Various Sizes On CT Images , 1985, Medical Imaging.

[12]  R G Swensson,et al.  Detection of small focal lesions in CT images: effects of reconstruction filters and visual display windows. , 1985, The British journal of radiology.

[13]  H. Barrett,et al.  Effect of noise correlation on detectability of disk signals in medical imaging. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[14]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[15]  R G Swensson,et al.  Measuring performance efficiency and consistency in visual discriminations with noisy images. , 1996, Journal of experimental psychology. Human perception and performance.

[16]  Philip F. Judy,et al.  Observer Efficiency And Feature Polarity , 1987, Medical Imaging.

[17]  R G Swensson,et al.  Flattening of the contrast-detail curve for large lesions on liver CT images. , 1994, Medical physics.

[18]  R D Nawfel,et al.  Contrast-detail curves for liver CT. , 1992, Medical physics.

[19]  John A. Swets,et al.  Evaluation of diagnostic systems : methods from signal detection theory , 1982 .