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Proceedings Paper

Assessment of automatic exposure control performance in digital mammography using a no-reference anisotropic quality index
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Paper Abstract

Automatic exposure control (AEC) is used in mammography to obtain acceptable radiation dose and adequate image quality regardless of breast thickness and composition. Although there are physics methods for assessing the AEC, it is not clear whether mammography systems operate with optimal dose and image quality in clinical practice. In this work, we propose the use of a normalized anisotropic quality index (NAQI), validated in previous studies, to evaluate the quality of mammograms acquired using AEC. The authors used a clinical dataset that consists of 561 patients and 1,046 mammograms (craniocaudal breast views). The results show that image quality is often maintained, even at various radiation levels (mean NAQI = 0.14 ± 0.02). However, a more careful analysis of NAQI reveals that the average image quality decreases as breast thickness increases. The NAQI is reduced by 32% on average, when the breast thickness increases from 31 to 71 mm. NAQI also decreases with lower breast density. The variation in breast parenchyma alone cannot fully account for the decrease of NAQI with thickness. Examination of images shows that images of large, fatty breasts are often inadequately processed. This work shows that NAQI can be applied in clinical mammograms to assess mammographic image quality, and highlights the limitations of the automatic exposure control for some images.

Paper Details

Date Published: 10 March 2017
PDF: 8 pages
Proc. SPIE 10136, Medical Imaging 2017: Image Perception, Observer Performance, and Technology Assessment, 101360U (10 March 2017); doi: 10.1117/12.2255629
Show Author Affiliations
Bruno Barufaldi, Univ. de São Paulo (Brazil)
Univ. of Pennsylvania (United States)
Lucas R. Borges, Univ. de São Paulo (Brazil)
Univ. of Pennsylvania (United States)
Predrag R. Bakic, Univ. of Pennsylvania (United States)
Marcelo A. C. Vieira, Univ. de São Paulo (Brazil)
Homero Schiabel, Univ. de São Paulo (Brazil)
Andrew D. A. Maidment, Univ. of Pennsylvania (United States)


Published in SPIE Proceedings Vol. 10136:
Medical Imaging 2017: Image Perception, Observer Performance, and Technology Assessment
Matthew A. Kupinski; Robert M. Nishikawa, Editor(s)

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