Reliable quality assurance of X-ray mammography scanner by evaluation the standard mammography phantom image using an interpretable deep learning model
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Abstract
<p class="first" id="d502765e99">Mammography is the initial examination to detect
breast cancer symptoms, and quality
control of mammography devices is crucial to maintain accurate diagnosis and to safeguard
against degradation of performance. The objective of this study was to assist radiologists
in mammography phantom image evaluation by developing and validating an interpretable
deep learning model capable of objectively evaluating the quality of standard phantom
images for mammography.
</p>