Objective:This study was aimed to investigate the reliability of a computer application for assessment of the stages of cervical vertebra maturation in order to determine the stage of skeletal maturity.Material and methods:For this study, digital lateral cephalograms of 99 subjects (52 females and 47 males) were examined. The following selection criteria were used during the sample composition: age between 9 and 16 years, absence of anomalies of the vertebrae, good general health, no history of trauma at the cervical region. Subjects with lateral cephalograms of low quality were excluded from the study. For the purpose of this study a computer application Cephalometar HF V1 was developed. This application was used to mark the contours of the second, third and fourth cervical vertebrae on the digital lateral cephalograms, which enabled a computer to determine the stage of cervical vertebral maturation. The assessment of the stages of cervical vertebral maturation was carried out by an experienced orthodontist. The assessment was conducted according to the principles of the method proposed by authors Hassel and Farman. The degree of the agreement between the computer application and the researcher was analyzed using by statistical Cohen Kappa test.Results:The results of this study showed the agreement between the computer assessment and the researcher assessment of the cervical vertebral maturation stages, where the value of the Cohen Kappa coefficient was 0.985.Conclusion:The computer application Cephalometar HF V1 proved to be a reliable method for assessing the stages of cervical vertebral maturation. This program could help the orthodontists to identify the stage of cervical vertebral maturation when planning the orthodontic treatment for the patients with skeletal disharmonies.
Shape, color and texture are the most important discriminative elements for content based image retrieval. Fourier descriptors are widely used in shape based image retrieval problems. This paper presents a novel method of extracting Fourier descriptors from the simplest shape signature -complex coordinates. Instead of the commonly used scale normalization with the magnitude of the first harmonic, normalization with the sum of magnitudes of all harmonics is used. This leads to an improved shape scale normalization. All the experimental results indicate that the proposed method outperforms many other stateof-the-art Fourier descriptors based methods, both in terms of retrieval performance and computational time.
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