KEYWORDS: Modulation transfer functions, Chromium, Digital mammography, Computing systems, Gold, Photon counting, Signal to noise ratio, Polymethylmethacrylate, Chest, Radiology
The purpose was to find the correlation between a Figure of Merit (FoM) calculated from a new (simple) test object for Quality Control in digital mammography and CDMAM threshold thicknesses. The FoM included the signal difference to noise ratio, modulation transfer function of the complete system (including scatter and grid) and normalized noise power spectrum. The pre-programmed exposure settings for clinical work were used, as was done for the CDMAM
acquisitions. The FoM is calculated from 2 images only (an image from the QC test object and an image of a corresponding homogeneous plate imaged with the same exposure settings). This FoM was evaluated in frequencies that match with the diameters of the gold disks in the CDMAM phantom. Computerized CDMAM analysis uses 16 images
per system. The software program "cdcom" (www.euref.org) was used for the 4-AFC experiment. All matrices were averaged, smoothed with a Gaussian filter and psychometric curves were fitted through the correctly detected fractions to obtain the threshold thickness with a detectability of 62.5% for all diameters.
Images have been acquired on 10 different systems (2 computed radiography (CR) systems, 6 direct radiology (DR) systems and 2 photon counting systems).
The reproducibility of the QC metrics from images of the new phantom was assessed. The standard error on the mean of the FoM was for the highest frequency 8.1% for a CR system and 5.6% for a DR system. The main component in this error is due to the NNPS and the limited number of independent pixels used in this analysis.
Parameters calculated from both phantoms are sensitive to variation in mean glandular dose levels. Present results show a weak correlation (R2=0.60) between the FoM at 5lp/mm and CDMAM threshold values for the 0.1mm objects when all system data are pooled. If evaluated for separate systems, the correlation holds promise for automated, periodic performance evaluations of digital mammography systems with the simplified phantom.
Purpose: To investigate the influence of physician-selectable equipment variables on image quality for a cardiac X-ray
system equipped with flat panel detector.
Materials and Methods: Two contrast phantoms (Leeds TO.10 and CDRAD) were imaged in fluorography and
fluoroscopy mode. Three variables are studied: the detector entrance dose, patient thickness and antiscatter grid. In
fluorography mode, the detector entrance dose was 100, 120, 140, 170, 200 and 240 nGy/image. Patient thickness was
simulated with Perspex blocks of 8, 12, 16 and 20cm. The detectability of contrast details was visually evaluated by five
observers (subjective method). An alternative objective method of image quality evaluation was used. It consists on
determining a simple "figure of merit" parameter based on signal-to-noise and dose measurements.
Results: The threshold contrast values were determined for different settings. Contrast-detail curves are presented.
Conversion of curve data in single numerical values and comparison with the "figure of merit" are discussed.
Conclusion: Contrast detail objects are sensitive to variables changed and can be used in optimization process of new
systems. The change of detector entrance dose from a superior to a next inferior setting does not change dramatically the
image quality. Consequently, a saving of about 15% in patient "skin" dose is achievable.
Purpose:
The purposes of the study were to set-up and validate a simulation framework for dose and image quality optimization
studies. In a first phase we have evaluated whether CDRAD images as obtained with computed radiography plates could
be simulated.
Material and Methods:
The Monte Carlo method is a numerical method that can be used to simulate radiation transport. It is in diagnostic
radiology often used in dosimetry, but in present study it is used to simulate X-ray images. With the Monte Carlo
software, MCNPX, the successive steps in the imaging chain were simulated: the X-ray beam, the attenuation and scatter
process in a test object and image generation by an ideal detector.
Those simulated images were further modified for specific properties of CR imaging systems. The signal-transfer-properties
were used to convert the simulated images into the proper grey scale. To account for resolution properties the
simulated images were convolved with the point spread function of the CR systems. In a last phase, noise, based on
noise power spectrum (NPS) measurements, was added to the image.
In this study, we simulated X-ray images of the CDRAD contrast-detail phantom. Those simulated images, modified for
the CR-system, were compared with real X-ray images of the CDRAD phantom. All images were scored by computer
readings.
Results:
First results confirm that realistic CDRAD images can be simulated and that reading results of series of simulated and
real images have the same tendency. The simulations also show that white noise has a large influence on image quality
and CDRAD analyses.
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