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Human observer detection experiments with mammograms and power‐law noise

Medical Physics · 2001 · Vol. 28(4) · pp. 419–437
Arthur E. BurgessFrancine L. JacobsonPhilip F. Judy

Abstract

We determined contrast thresholds for lesion detection as a function of lesion size in both mammograms and filtered noise backgrounds with the same average power spectrum, P(f)=B/f3. Experiments were done using hybrid images with digital images of tumors added to digitized normal backgrounds, displayed on a monochrome monitor. Four tumors were extracted from digitized specimen radiographs. The lesion sizes were varied by digital rescaling to cover the range from 0.5 to 16 mm. Amplitudes were varied to determine the value required for 92% correct detection in two-alternative forced-choice (2AFC) and 90% for search experiments. Three observers participated, two physicists and a radiologist. The 2AFC mammographic results demonstrated a novel contrast-detail (CD) diagram with threshold amplitudes that increased steadily (with slope of 0.3) with increasing size for lesions larger than 1 mm. The slopes for prewhitening model observers were about 0.4. Human efficiency relative to these models was as high as 90%. The CD diagram slopes for the 2AFC experiments with filtered noise were 0.44 for humans and 0.5 for models. Human efficiency relative to the ideal observer was about 40%. The difference in efficiencies for the two types of backgrounds indicates that breast structure cannot be considered to be pure random noise for 2AFC experiments. Instead, 2AFC human detection with mammographic backgrounds is limited by a combination of noise and deterministic masking effects. The search experiments also gave thresholds that increased with lesion size. However, there was no difference in human results for mammographic and filtered noise backgrounds, suggesting that breast structure can be considered to be pure random noise for this task. Our conclusion is that, in spite of the fact that mammographic backgrounds have nonstationary statistics, models based on statistical decision theory can still be applied successfully to estimate human performance.

AI in cancer detectionDigital Radiography and Breast ImagingInfrared Target Detection MethodologiesNoise (video)MathematicsObserver (physics)Contrast (vision)Two-alternative forced choiceArtificial intelligenceOpticsComputer visionPhysicsComputer science

MeSH terms

FemaleHumansImage Processing, Computer-AssistedMammographyReproducibility of ResultsModels, StatisticalObserver Variation
Citations
448
FWCI
10.97
field-weighted impact
References
73
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98%
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References
A four mechanism model for threshold spatial vision
Vision Research · 1979 · 712 citations
Visible differences predictor: an algorithm for the assessment of image fidelity
Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992 · 704 citations
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