牙列早期发育的三维重建分析

Cui Ling-ling
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引用次数: 0

摘要

三维重建已广泛应用于医学疾病诊断领域,行军立方体算法是面对三维重建最具代表性的结构。因此,采用三维重建的方法来可视化发育结构的表面形态,并有助于了解早期牙齿形态发生的复杂性。本文介绍了MCalgorithm的基本原理,提出了一种基于优化网格模型的简化算法。简化算法选择的点尽可能靠近原始网格,通常采用子集选择法或优化选择法。这些基本器官可以挽救它们被抑制的发育并恢复活力,然后它们随后的自主发展可以引起口腔病理。这表明,哺乳动物的牙齿形成潜力可能比从它们的功能牙列中观察到的要大。从这个角度来看,小鼠初级牙齿原基是测试牙齿再生可能性的自然模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
3D Reconstructions Analysis of the Early Development of the Dentition
3D Reconstructions has been widely used in the field of medical disease diagnosis and Marching Cube algorithm is the most representative structure in the face of 3D reconstructions. Therefore, methods of three-dimensional (3D) reconstructions were employed to visualize the surface morphology of developing structures and to help appreciate the complexity of early tooth morphogenesis. The authors introduce in the paper the principle of MCalgorithm, and present a simplified algorithm based on optimized grid model. The simplified algorithm selects points as close tooriginal grid as possible, usually using the subset selection method or the optimized selection method. The rudiments can rescue their suppressed development and revitalize, and then their subsequent autonomous development can give rise to oral pathologies. This shows that tooth-forming potential in mammals can be greater than that observed from their functional dentitions. From this perspective, the mouse rudimentary tooth primordia represent a natural model to test possibilities of tooth regeneration.
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