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Bart Truyen, Peter Bottenberg, Bogdan Nitulescu, Cristina Boca, Jan Cornelis
 

Caries Research

Contribution To Journal

Abstract 

Despite the questionable sensitivity of conventional radiographic evaluation for slowly progressing proximal caries, application of digital subtraction imaging, with its much improved performance for revealing subtle changes in mineralization, has not seen general clinical acceptance. This reluctance may be attributed to the non-trivial user-involvement required in the retrospective correction for discrepancies in projective geometry between serial radiographs. The aim of this study was to compare the performance of a mutual information based automated method for retrospective geometric standardization, with a manual reference point method, and another automated method alike [Yoon D: Dentomaxillofac Radiol 2000, 29:11-19]. To investigate the influence of horizontal angulation errors on the performance of the reconstruction, a series of radiographs of the molar region of a preserved human mandible were taken that differed with a preliminary recorded reference image by 0-8 degrees in angular position of the object. This produces geometric inconsistencies similar to those observed in clinically acquired serial radiographs, but violating the projective model underlying the correction methods. All geometric reconstructions were repeated 4 times. Radiographs were recorded on storage phosphor plates and digitized using a Digora fmx-DXR40 system (Soredex, Helsinki, Finland). Performance of the geometric standardization was measured by calculating the standard deviation of the gray values in the difference image obtained by subtracting the geometrically corrected image from the reference image. Differences between the 3 methods were evaluated by paired t tests. For all angulations evaluated, the new method was found to improve significantly upon the performance of the 2 existing methods, reducing the distance measure by as much as 40%. Also, the performance of the new method seemed to degrade less rapidly as a function of the angular disparity (Spearman’s correlation analysis).

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DOI Link