Objective: The purpose of this study was to evaluate the semiautomatic alignment and correction of affine geometric discrepancies for digital subtraction radiography.
Study Design: Algorithms were tested in vitro to determine their ability to semiautomatically select reference points on a second image based on points selected on a first (reference) image. A preserved human mandible was imaged with and without bone-equivalent material chips at varying degrees of angulation. Each chip had a mass of less than 10 mg and was no more than 0.3 mm thick. High levels of specificity and sensitivity for chip detection were achieved with 6 degrees of angular discrepancy or less. The algorithms were then applied to radiographs from six human subjects through use of the bone-chip validation model.
Results: Sensitivity was 89% and 100% for the three-point and four-point affine warp algorithms, respectively. Specificity for both algorithms was 100%.
Conclusions: The data indicate that semiautomated alignment algorithms may enhance the efficacy of digital subtraction radiography while maintaining diagnostic efficacy in clinical trials.
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