computer software

Radiographs, adjunct to clinical examination are always valuable complementary methods for dental caries detection. Recently, progressing in digital imaging system provides possibility of software designing for automatically dental caries detection.. The aim of this study was to develop and assess the function of diagnostic computer software designed for evaluation of approximal caries in posterior teeth. This software should be able to indicate the depth and location of caries on digital radiographic images.. Digital radiographs were obtained of 93 teeth including 183 proximal surfaces. These images were used as a database for designing the software and training the software designer. In the design phase, considering the summed density of pixels in rows and columns of the images, the teeth were separated from each other and the unnecessary regions; for example, the root area in the alveolar bone was eliminated. Therefore, based on summed intensities, each image was segmented such that each segment contained only one tooth. Subsequently, based on the fuzzy logic, a well-known data-clustering algorithm named fuzzy c-means (FCM) was applied to the images to cluster or segment each tooth. This algorithm is referred to as a soft clustering method, which assigns data elements to one or more clusters with a specific membership function. Using the extracted clusters, the tooth border was determined and assessed for cavity. The results of histological analysis were used as the gold standard for comparison with the results obtained from the software. Depth of caries was measured, and finally Intraclass Correlation Coefficient (ICC) and Bland-Altman plot were used to show the agreement between the methods.. The software diagnosed 60% of enamel caries. The ICC (for detection of enamel caries) between the computer software and histological analysis results was determined as 0.609 (95% confidence interval [CI] = 0.159-0.849) (P = 0.006). Also, the computer program diagnosed 97% of dentin caries and the ICC between the software and histological analysis results for dentin caries was determined as 0.937 (95% CI=0.906-0.958) (P < 0.001). Bland-Altman plot showed an acceptable agreement for measuring the depth of caries in enamel and dentin.. The designed software was able to detect a significant number of dentin caries and acceptable measuring of the depth of carious lesions in enamel and dentin. However, the software had limited ability in detecting enamel lesions..

Statement of Problem: Evaluation of diagnostic records as a supplement to direct examination has an important role in treatment planning of orthodontic patients with aesthetic needs. Photogrammetry as a quantitative tool has recently attracted the attention of researchers again. The purpose of this study was to design computer software to analyze orthodontic patients’ facial profile photographic images and to estimate reliability and validity of its measurement. Profile photographic images of 20 volunteered students were taken in the natural head position with standard technique. Manual linear and angular measurements were used as a gold standard and compared with the results obtained from Aesthetic analyzer Software (designed for that purpose). Dahlberg’s method error and Intraclass Correlation Coefficient (ICC) was used to estimate validity, reliability and inter-examiner errors. Almost all the measurements showed a high correlation between the manual and computerized method (ICC>0.75). The maximum method errors computed from Dahlberg’s formula were 1.345 mm in linear and 3.294 degrees in angular measurements. At the highest levels, inter-examiner errors were 1.684 mm and 3.741 degrees in linear and angular measurements, respectively. Although a low budget has been allocated for the design of Aesthetic Analyzer software, its features are comparable with commercially available products. The software’s capabilities can be increased. The results of the current study indicated that the software is accurate and repeatable in photographic analysis of orthodontic patients.