Changes in practice have led to higher values for patient x-ray radiation exposures during cardiac catheterization procedures. The real-time display and recording of x-ray exposure facilitates the reduction of exposure in the catheterization laboratory.

Artefacts on radiographic images are distracting and may compromise accurate diagnosis. Although most artefacts that occur in conventional radiography have become familiar, computed radiography (CR) systems produce artefacts that differ from those found in conventional radiography. We have encountered a variety of artefacts in CR images that were produced from four different models plate reader. These artefacts have been identified and traced to the imaging plate, plate reader, image processing software or laser printer or to operator error. Understanding the potential sources of CR artefacts will aid in identifying and resolving problems quickly and help prevent future occurrences.

Our goal in this work was to compare the results of common phantom tests made using matched and mixed ultrasound (US) scanner‐transducer combinations. Sets of common US quality assurance (QA) measurements were made using matched US scanner‐transducer combinations (i.e., transducers purchased for use with a particular scanner), as well as unmatched (mixed) combinations. Measurements of vertical and horizontal distance accuracy, and depth of penetration were performed using three common transducer types. Means, standard deviations, and differences between the mean mix and match measurements divided by the standard deviation (match‐mix difference, or MMD), and two‐sided, paired t‐tests were computed for the groups of mixed and matched measurements. MMDs for vertical and horizontal distance accuracy test results were less than 0.87 in all cases, well below our threshold value of 2.0, which indicates that a significant difference exists. MMDs for the depth of penetration measurements were less than 1.50, again below the threshold value. These results suggest that all of the mixed and matched data sets were very similar. The more sensitive t‐tests indicate statistically significant differences in only 2 of the 18 pairs of data sets. In conclusion, this study suggests that QA measurements generated by mixed or matched scanner‐transducer combinations are very comparable. The ability to obtain QA phantom test data from mixed scanner‐transducer combinations reduces the time required for US QA testing.PACS number(s): 87.57.–s, 87.62.+n

Nine moderately priced frame-grabber boards for both Macintosh (Apple Computers, Cupertino, CA) and IBMcompatible computers were evaluated using a Society of Motion Pictures and Television Engineers (SMPTE) pattern and a video signal generator for dynamic range, gray-scale reproducibility, and spatial integrity of the captured image. The degradation of the vŸ information ranged from minor to severe. Some boards are of reasonable quality for applications in diagnostic imaging and education. However, price and quality ate not necessarily directly related. Copyright 9 1995by W.B. Saunders Company imaging chain that can alter the image information. In conventional diagnostic radiologic quality control, an effort is made to assure that image degradation caused by any component of the imaging chain is understood and minimized. 1,2 Extrapolation of this concept to computer-aided image analysis dictates that the additional items in the imaging chain, namely the vŸ camera, digitizing process, and display must also be subject to such scrutiny.KEY WORDS: quality control, video, frame grabber, personal computers, analog devices, picture archiving and communication systems (PACS).

A noninvasive method was developed for quantifying the overall contrast of fluoroscopic imaging systems within the clinical setting by using a simple phantom and common video test equipment. In this method, an acrylic phantom with four holes filled with varying amounts of air and aluminum is placed on the entrance exposure side of a patient-equivalent acrylic phantom. The air-and aluminum-filled holes provide a stepped gray-scale pattern that is displayed on the examination room viewing monitor when the phantom is fluoroscopically imaged under automatic brightness control. A video waveform monitor or oscilloscope is then used to quantify those video signal voltage levels as a contrast index value, which is defined as the maximum range of the video signal voltage levels of the gray-scale steps. The method is repeatable and allows quantification of the contrast of the imaging system. It can also be used to optimize video parameters, provide comparative data for quality control monitoring, and characterize overall contrast differences between systems. Experience with this method suggests that there is excellent correlation between the clinical perception of image contrast and the contrast index, with contrast index changes of approximately 15% being seen clinically.