Primary Tooth Extraction Pattern Among Turkish Children with Severe Early Childhood Caries Treated Under General Anesthesia

Predictors of Parental Acceptance towards Contemporary Behavior Management Techniques Used in Pediatric Dentistry: A Preliminary Study on Turkish Population

BACKGROUND

Parents, who make the final decision regarding their child's treatment, play a significant role in their dental care. Parental approval is important for each stage of treatment and may affect the physician's approach to the treatment. Therefore, it is essential for pediatric dentists to comprehend which behavior management techniques (BMTs) are acceptable to parents and to identify the factors that influence their acceptability.

METHODS

Parents who were bringing their children for dental treatment answered a survey on the acceptance of twenty contemporary BMTs. The sociodemographic data of the parents and the age, gender, and Frankl behavior rating scale (Frankl) scores of their children were recorded. Parents were asked to indicate their level of acceptance of each BMT. Binary logistic regression analysis was designed to see the predictors of "accepted" and "declined" answers.

RESULTS

According to acceptance frequencies, the most accepted technique was communication and communicative guidance. The most declined technique was parental absence. The child's age, gender, Frankl score, parental educational status, and parent type predict the acceptability of some BMTs.

CONCLUSION

This study revealed that pediatric dentists must consider parent and child factors when selecting BMTs for children. We believe that this study can provide a basis for determining which factors pediatric dentists should consider when selecting individualized BMTs.

A Systematic Study on the Extraction and Image Reproduction of Ceramic Sculpture Artworks

In order to solve the research on the extraction of ceramic sculpture artwork patterns, and, in the process of image reproduction, the problem of too few feature points in the object image, the author proposes an image stitching algorithm that combines SIFT and MSER algorithms. After comprehensively analyzing the principles, advantages, and disadvantages of the current main image stitching methods, in terms of feature matching, based on the K-D tree search algorithm, the improved BBF algorithm is used to improve the search efficiency of feature points. In order to remove the possible cracks in the stitching process, an improved multiband fusion algorithm is used to seamlessly stitch the registered images. The results show that the feature points detected by the one-dimensional normal distribution algorithm are on average 0.1%, 0.5%, 1.7%, 4.4%, and 9.2%. The algorithm combining SIFT and MSER to extract feature points can reach 3.6%, 4.6%, 8.4%, 15%, and 19.1%. The experimental results show that the algorithm proposed by the author can extract more image feature points to facilitate later image registration. The image blur phenomenon in the original image fusion algorithm is solved, and a complete and clear two-dimensional plane pattern is finally obtained.