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相关概念视频

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...

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相关实验视频

Updated: Jul 25, 2026

Modeling and Simulations of Olfactory Drug Delivery with Passive and Active Controls of Nasally Inhaled Pharmaceutical Aerosols
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构建鼻腔假肢形态数据基于一个非刚性注册算法.

Aonan Wen1, Xiaohui Zhang2, Yong Wang3

  • 1Doctoral student, Center of Digital Dentistry/Department of Prosthodontics, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology & NHC Key Laboratory of Digital Stomatology, Beijing, PR China.

The Journal of prosthetic dentistry
|April 8, 2025
PubMed
概括

普罗克鲁斯特分析-非刚性代式最接近点 (PA-NICP) 算法为鼻假体数据构建提供了改进的边缘紧密性和形态过渡. 这种数字方法有助于恢复鼻缺陷患者的面部完整性.

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Real-Time Dynamic Navigation System for the Precise Quad-Zygomatic Implant Placement in a Patient with a Severely Atrophic Maxilla
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Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
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相关实验视频

Last Updated: Jul 25, 2026

Modeling and Simulations of Olfactory Drug Delivery with Passive and Active Controls of Nasally Inhaled Pharmaceutical Aerosols
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科学领域:

  • 医疗工程 医学工程
  • 计算机辅助设计 计算机辅助设计
  • 生物医学成像技术 生物医学成像技术

背景情况:

  • 鼻子假肢对于恢复鼻子缺陷患者的面部形态至关重要.
  • 鼻子假肢的数字设计和制造需要准确的形态数据,但相关研究很少.
  • 开发有效的方法来构建鼻腔假体形态对于成功的修复结果至关重要.

研究的目的:

  • 评估Procrustes分析-非刚性代式最接近点 (PA-NICP) 算法,用于快速构建鼻子假肢形态数据.
  • 为了比较PA-NICP算法与MeshMonk程序在生成鼻子假肢数据方面的有效性.
  • 评估数字假肢设计的非刚性注册原则.

主要方法:

  • 使用3D面部扫描仪收集了30名成年男性的3D面部数据.
  • 使用Geomagic Wrap 2021构建了30个总鼻腔缺陷3D面部数据集.
  • 应用了PA-NICP算法 (实验) 和MeshMonk程序 (控制) 来生成鼻子假肢数据,比较3D偏差,边缘紧密性和表面连续性.

主要成果:

  • 在PA-NICP (1.51 ±0.45毫米) 和MeshMonk (1.34 ±0.31毫米) (P=.054) 之间,3D形态偏差 (RMS) 没有显著差异.
  • PA-NICP表现出明显更好的边缘紧密性 (RMS偏差为0.22 ±0.05毫米而不是0.38 ±0.09毫米;P<.001).
  • PA-NICP显示了明显更高的边缘表面连续性 (95.47%与92.20%相比;P=.001).

结论:

  • 无论是PA-NICP还是MeshMonk,都有效地构建了鼻子假肢数据.
  • 与MeshMonk相比,PA-NICP算法提供了优越的边缘紧密性和形态过渡.
  • PA-NICP是数字鼻腔假体设计和制造的一个有前途的工具.