KEYWORDS: Modulation transfer functions, Gold, Sensors, Digital mammography, Signal to noise ratio, Mammography, Detection and tracking algorithms, Image processing, Data modeling, Spatial frequencies
CDMAM phantoms are widely used in the Europe to assess the performance of mammography systems
utilising small size and low contrast disc details. However, the assessment of CDMAM images by human
observers is slow and tedious. An automated method for scoring CDMAM images (CDCOM) is widely
available to address this issue. We have developed an alternative automated scoring tool to score CDMAM
images, Quantitative Assessment System (QAS), for similarly removing inter- and intra- observer variability.
This provides additional valuable information about the contrast and SNR of each gold disc within the
image. The QAS scores CDMAM phantom images using a scanning algorithm. QAS scoring results were
compared with human observers and with CDCOM. It was found that QAS was comparable with human
observers in scoring, whereas CDCOM consistently scored a higher number of discs correctly in CDMAM
images compared with QAS and human observers.
QAS results have been used to analyse the effects of different digital mammography system modulation
transfer functions (MTFs) on fine details for a number of systems in the form of contrast degradation factor
(CDF) measurements. CDF curves for experimentally acquired CDMAM images were compared with those
for simulated CDMAM images to assess the accuracy of contrast measurements.
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