Computer-aided image analysis in dentistry is a promising tool for detecting and monitoring disease changes and treatment planning. In recent years, two 3D imaging techniques have gained prominence, namely CBCT and 3D optical scanning. The fusion of the data obtained by these two imaging techniques and the improvements in the analysis represent an unexplored possibility to evaluate the oral cavity's hard and soft tissue changes. This doctoral dissertation by publication aimed to develop new approaches and methods for accurately evaluating localised changes of the oral cavity's hard and soft tissues through computer-aided 3D image analysis. The dissertation deals with the alignment and analysis steps of computer-aided image analysis in prosthodontics and periodontology.
The spatial alignment of the images provides the basis for further detailed analysis of the changes. In the two involved clinical fields, we empirically confirmed through two methodological studies that we have present stable regions that increase the precision of the spatial alignment of 3D images of the oral cavity.
In prosthodontics, we demonstrated new possibilities for comprehensively evaluating localised changes of denture-supporting tissues. By computing the distances between the surfaces of four aligned 3D models acquired at two different times and with two different modalities, we can accurately evaluate the changes and thickness of individual tissues and the dynamics of these tissues.
In periodontology, we demonstrated the potential of direct and precise evaluation of gingival margin changes. Using spatially aligned 3D images, shape analysis, which can precisely determine the measurement reference points, and calculating the distances between these points, changes in gingival margin level can be directly evaluated without using CEJ as a reference structure. Comparison with a clinically established method showed a more accurate evaluation, mainly due to the higher resolution and the exclusion of the CEJ as a critical reference structure. At the same time, we have shown that shape analysis can also be used as an objective method to evaluate gingival shape in detecting inflammation.
In computer-aided 3D image analysis, a clinical understanding of localised hard and soft tissue changes is essential for adapting concepts and methods to specific fields of dentistry. Furthermore, optimisation of the methods significantly increases the accuracy and thus allows new possibilities and improvements for detecting and monitoring disease changes and treatment planning.
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