63 resultados para Distance exercised
em BORIS: Bern Open Repository and Information System - Berna - Suiça
Resumo:
Our aim in this study was to compare intermolar widths after alignment of crowded mandibular dental arches in nonextraction adolescent patients between conventional and self-ligating brackets.
Resumo:
Purpose Orthognathic surgery has the objective of altering facial balance to achieve esthetic results in patients who have severe disharmony of the jaws. The purpose was to quantify the soft tissue changes after orthognathic surgery, as well as to assess the differences in 3D soft tissue changes in the middle and lower third of the face between the 1- and 2-jaw surgery groups, in mandibular prognathism patients. Materials and Methods We assessed soft tissue changes of patients who have been diagnosed with mandibular prognathism and received either isolated mandibular surgery or bimaxillary surgery. The quantitative surface displacement was assessed by superimposing preoperative and postoperative volumetric images. An observer measured a surface-distance value that is shown as a contour line. Differences between the groups were determined by the Mann-Whitney U test. The Spearman correlation coefficient was used to evaluate a potential correlation between patients' surgical and cephalometric variables and soft tissue changes after orthognathic surgery in each group. Results There were significant differences in the middle third of the face between the 1- and 2-jaw surgery groups. Soft tissues in the lower third of the face changed in both surgery groups, but not significantly. The correlation patterns were more evident in the lower third of the face. Conclusion The overall soft tissue changes of the midfacial area were more evident in the 2-jaw surgery group. In 2-jaw surgery, significant changes would be expected in the midfacial area, but caution should be exercised in patients who have a wide alar base.
Resumo:
The task considered in this paper is performance evaluation of region segmentation algorithms in the ground-truth-based paradigm. Given a machine segmentation and a ground-truth segmentation, performance measures are needed. We propose to consider the image segmentation problem as one of data clustering and, as a consequence, to use measures for comparing clusterings developed in statistics and machine learning. By doing so, we obtain a variety of performance measures which have not been used before in image processing. In particular, some of these measures have the highly desired property of being a metric. Experimental results are reported on both synthetic and real data to validate the measures and compare them with others.