This research will study and compare observers' performance in a variety of prototypical detection and feature-discrimination tasks, using high-quality digital images with uncorrelated-noise backgrounds. The estimates of human observers' detection and discrimination capabilities will also be compared with the ideal observer's capability to perform the same decision task with the same physical images. This will permit estimates of observers' efficiency, relative to the maximum possible performance. Our previous research with CT images indicates that changes in observers' ability to detect lesions on those images can be predicted by the performance of a physical cross-correlator, across a wide variety of manipulations of the physical image properties. This research will extend our previous investigations to images in which the cross-correlator is an optimum physical calculation, and to tasks that are more complex than feature detection. The measurements of observer efficiency will be interpreted by a model of the human observer, which attributes the observer's reduced efficiency to a combination of systematic factors and unsystematic sources of variability (observer noise). This model of the observer will be developed and tested in detection and discrimination tasks, whose conditions are deliberately designed: (a) to manipulate potential systematic and unsystematic sources of observer inefficiencies, and (b) to alter the relative importance of the physical-noise and observer-noise in limiting the observer's ability to perform the decision task. The proposed research will also develop and test new ROC methods for evaluating a combination of the observer's likelihood ratings and identification judgments in task that present more than two specified alternatives.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA043114-02
Application #
3185041
Study Section
Diagnostic Radiology Study Section (RNM)
Project Start
1986-08-01
Project End
1991-05-31
Budget Start
1987-06-01
Budget End
1988-05-31
Support Year
2
Fiscal Year
1987
Total Cost
Indirect Cost
Name
Brigham and Women's Hospital
Department
Type
DUNS #
071723621
City
Boston
State
MA
Country
United States
Zip Code
02115
Swensson, R G (2000) Using localization data from image interpretations to improve estimates of performance accuracy. Med Decis Making 20:170-85
Wester, C; Judy, P F; Polger, M et al. (1997) Influence of visual distractors on detectability of liver nodules on contrast-enhanced spiral computed tomography scans. Acad Radiol 4:335-42
Swensson, R G (1996) Unified measurement of observer performance in detecting and localizing target objects on images. Med Phys 23:1709-25
Swensson, R G; Judy, P F (1996) Measuring performance efficiency and consistency in visual discriminations with noisy images. J Exp Psychol Hum Percept Perform 22:1393-415
Seltzer, S E; Judy, P F; Adams, D F et al. (1995) Spiral CT of the chest: comparison of cine and film-based viewing. Radiology 197:73-8
Seltzer, S E; Judy, P F; Swensson, R G et al. (1994) Flattening of the contrast-detail curve for large lesions on liver CT images. Med Phys 21:1547-55
Nawfel, R D; Chan, K H; Wagenaar, D J et al. (1992) Evaluation of video gray-scale display. Med Phys 19:561-7
Judy, P F; Swensson, R G; Nawfel, R D et al. (1992) Contrast-detail curves for liver CT. Med Phys 19:1167-74
Seltzer, S E; Swensson, R G; Nawfel, R D et al. (1991) Visualization and detection-localization on computed tomographic images. Invest Radiol 26:285-94
Swensson, R G; Theodore, G H (1990) Search and nonsearch protocols for radiographic consultation. Radiology 177:851-6

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