Fundamentals of digital image processing
Fundamentals of digital image processing
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The use of digital mammography systems has become widespread recently However, the optimal exposure parameters are uncertain in clinical practice We need to optimize the exposure parameter in digital mammography while maximizing image quality and minimizing patient dose The purpose of this study was to evaluate the most beneficial exposure variable—tube voltage for each compressed breast thickness—with these indices: noise power spectrum, noise equivalent quanta, detective quantum efficiency, and signal-to-noise ratios (SNR) In this study, the SNRs were derived from the perceived statistical decision theory model with the internal noise of eye-brain system (SNRi), contrived and studied by Loo LN [1], Ishida M et al [2] These image quality indices were obtained under a fixed average glandular dose (AGD) and a fixed image contrast Our results indicated that when the image contrast and AGD was constant, for phantom thinner than 5 cm, an increase of the tube voltage did not improve the noise property of images very much The results also showed that image property with the target/filter Mo/Rh was better than that with Mo/Mo for phantom thicker than 4 cm In general, it is said that high tube voltage delivers improved noise property Our result indicates that this common theory is not realized with the x-ray energy level for mammography.