Analyzing the effect of dose reduction on the detection of mammographic lesions using mathematical observer models

Amarpreet S. Chawla; Robert Saunders; Craig Abbey; David Delong; Ehsan Samei

doi:10.1117/12.656378

17 March 2006 Analyzing the effect of dose reduction on the detection of mammographic lesions using mathematical observer models

Amarpreet S. Chawla, Robert Saunders, Craig Abbey, David Delong, Ehsan Samei

Author Affiliations +

Proceedings Volume 6146, Medical Imaging 2006: Image Perception, Observer Performance, and Technology Assessment; 61460I (2006) https://doi.org/10.1117/12.656378
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

The purpose of this study was to determine the effect of dose reduction on the detectability of breast lesions in mammograms. Mammograms with dose levels corresponding to 50% and 25% of the original clinically-relevant exposure levels were simulated. Detection of masses and microcalicifications embedded in these mammograms was analyzed by four mathematical observer models, namely, the Hotelling Observer, Non-prewhitening Matched Filter with Eye Filter (NPWE), and Laguerre-Gauss and Gabor Channelized Hotelling Observers. Performance was measured in terms of ROC curves and Area under ROC Curves (AUC) under Signal Known Exactly but Variable Tasks (SKEV) paradigm. Gabor Channelized Hotelling Observer predicted deterioration in detectability of benign masses. The other algorithmic observers, however, did not indicate statistically significant differences in the detectability of masses and microcalcifications with reduction in dose. Detection of microcalcifications was affected more than the detection of masses. Overall, the results indicate that there is a potential for reduction of radiation dose level in mammographic screening procedures without severely compromising the detectability of lesions.

Citation Download Citation

Amarpreet S. Chawla, Robert Saunders, Craig Abbey, David Delong, and Ehsan Samei "Analyzing the effect of dose reduction on the detection of mammographic lesions using mathematical observer models", Proc. SPIE 6146, Medical Imaging 2006: Image Perception, Observer Performance, and Technology Assessment, 61460I (17 March 2006); https://doi.org/10.1117/12.656378

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