Abstract
The detection of abnormalities in screening mammograms requires the highest possible image quality standards, since such abnormalities lie at the limit of physical detection. Image quality is currently assessed in the UK by imaging test objects most of which use a scoring system to gauge the visibility of details. This assessment is clearly subjective and open to inconsistencies over time and between observers. Image processing techniques were used to investigate the feasibility of automating the assessment of image quality. Test object radiographs were digitized using a Lumysis laser digitizer and a dedicated assessment procedure was developed to detect features within the image. Two methods were developed which identified and located test object details and were compared to human observers scoring the same test object radiograph. Contrast detail curves were used to compare all performances. The computer methods compared well with the human observers when identifying small details of less than 1 mm but were less successful in locating larger diameter details.
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