Comparison of edge analysis techniques for the determination of the MTF of digital radiographic systems.
The modulation transfer function (MTF) is well established as a metric to characterize the resolution performance of a digital radiographic system. Implemented by various laboratories, the edge technique is currently the most widespread approach to measure the MTF. However, there can be differences in the results attributed to differences in the analysis technique employed. The objective of this study was to determine whether comparable results can be obtained from different algorithms processing identical images representative of those of current digital radiographic systems. Five laboratories participated in a round-robin evaluation of six different algorithms including one prescribed in the International Electrotechnical Commission (IEC) 62220-1 standard. The algorithms were applied to two synthetic and 12 real edge images from different digital radiographic systems including CR, and direct- and indirect-conversion detector systems. The results were analysed in terms of variability as well as accuracy of the resulting presampled MTFs. The results indicated that differences between the individual MTFs and the mean MTF were largely below 0.02. In the case of the two simulated edge images, all algorithms yielded similar results within 0.01 of the expected true MTF. The findings indicated that all algorithms tested in this round-robin evaluation, including the IEC-prescribed algorithm, were suitable for accurate MTF determination from edge images, provided the images are not excessively noisy. The agreement of the MTF results was judged sufficient for the measurement of the MTF necessary for the determination of the DQE.
Duke Scholars
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Related Subject Headings
- Sensitivity and Specificity
- Reproducibility of Results
- Radiographic Image Interpretation, Computer-Assisted
- Radiographic Image Enhancement
- Quality Assurance, Health Care
- Phantoms, Imaging
- Pattern Recognition, Automated
- Nuclear Medicine & Medical Imaging
- Equipment Failure Analysis
- Algorithms
Citation
Published In
DOI
ISSN
Publication Date
Volume
Issue
Start / End Page
Location
Related Subject Headings
- Sensitivity and Specificity
- Reproducibility of Results
- Radiographic Image Interpretation, Computer-Assisted
- Radiographic Image Enhancement
- Quality Assurance, Health Care
- Phantoms, Imaging
- Pattern Recognition, Automated
- Nuclear Medicine & Medical Imaging
- Equipment Failure Analysis
- Algorithms