Paper
16 March 2011 Evaluation of the quality of image for various breast composition and exposure conditions in digital mammography
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Abstract
Breast density has a close relationship with breast cancer risk. The exposure parameters must be appropriately chosen for each breast. However, the optimal exposure conditions for digital mammography are uncertain in clinical. The exposure parameters in digital mammography must be optimized with maximization of image quality and minimization of radiation dose. We evaluated image quality under different exposure conditions to investigate the most advantageous tube voltage. For different compressed breast phantom thicknesses and compositions, we measured the Wiener spectrum (WS), noise-equivalent number of quanta (NEQ), and detective quantum efficiency (DQE). In this study, the signal-to-noise ratios were derived from a perceived statistical decision theory model with the internal noise of eye-brain system (SNRi), contrived and studied by Loo et al.1 and Ishida et al.2 These were calculated under a fixed average glandular dose. The WS values were obtained with a fixed image contrast. For 4-cm-thick and 50% glandular breast phantoms, the NEQ showed that high voltages gave a superior noise property of images, especially for thick breasts, but the improvement in the NEQ by tube voltage was not so remarkable. On the other hand, the SNRi value with a Mo filter was larger than that with a Rh filter. The SNRi increased when the tube voltage decreased. The result differed from those of WS and NEQ. In this study, the SNRi depended on the contrast of signal. Accuracy should be high with an intense, low-contrast object.
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Maki Yamada, Yuri Kato, Naotoshi Fujita, and Yoshie Kodera "Evaluation of the quality of image for various breast composition and exposure conditions in digital mammography", Proc. SPIE 7961, Medical Imaging 2011: Physics of Medical Imaging, 79615D (16 March 2011); https://doi.org/10.1117/12.877871
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KEYWORDS
Breast

Signal to noise ratio

Image quality

Modulation transfer functions

Digital mammography

X-rays

Spatial frequencies

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