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Since the video monitor is widely believed to be the weak link in the imaging chain, it is critical, to include it in the total image quality evaluation. Yet, most physical measurements of mammographic image quality are presently limited to making measurements on the digital matrix, not the displayed image. A method is described to quantitatively measure image quality of mammographic monitors using ACR phantom-based test patterns. The image of the test pattern is digitized using a charge coupled device (CCD) camera, and the resulting image file is analyzed by an existing phantom analysis method (Computer Analysis of Mammography Phantom Images, CAMPI). The new method is called CCD-CAMPI and it yields the Signal-to-Noise-Ratio (SNR) for an arbitrary target shape (e.g., speck, mass or fiber). In this work we show the feasibility of this idea for speck targets. Also performed were physical image quality characterization of the monitor (so-called Fourier measures) and analysis by another template matching method due to Tapiovaara and Wagner (TW) which is closely related to CAMPI. The methods were applied to a MegaScan monitor. Test patterns containing a complete speck group superposed on a noiseless background were displayed on the monitor and a series of CCD images were acquired. These images were subjected to CCD-CAMPI and TW analyses. It was found that the SNR values for the CCD-CAMPI method tracked those of the TW method, although the latter measurements were considerably less precise. The TW SNR measure was also about 25% larger than the CCD-CAMPI determination. These differences could be understood from the manner in which the two methods evaluate the noise. Overall accuracy of the CAMPI SNR determination was 4.1% for single images when expressed as a coefficient of variance. While the SNR measures are predictable from the Fourier measures the number of images and effort required is prohibitive and it is not suited to Quality Control (QC). Unlike the Fourier measures and the TW method, CCD-CAMPI is capable of yielding speck SNR on a single image. This is based on preliminary work and more complete testing is underway. Based on the early promising results, we expect that the CCD-CAMI method can be adapted to routine image QC of monitors using inexpensive equipment.
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