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相关概念视频

Tooth Anatomy01:21

Tooth Anatomy

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The human tooth enables us to eat a variety of foods, speak clearly, and even aid in shaping our faces. Teeth are composed of various elements that work together. Here's a detailed look at the anatomy of a human tooth.
The Crown, Neck, and Root
The visible part of the tooth is referred to as the crown. It's covered by enamel, the hardest substance in the human body. The crown is uniquely shaped for each type of tooth, allowing for different functions such as cutting, tearing, or...
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相关实验视频

Updated: May 5, 2026

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
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两个阶段的深度学习框架用于封闭冠深度图像生成.

Junghyun Roh1, Junhwi Kim2, Jimin Lee3

  • 1Graduate School of Artificial Intelligence, Ulsan National Institute of Science and Technology, 50, UNIST-gil, Ulsan, 44919, Republic of Korea.

Computers in biology and medicine
|October 4, 2024
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概括
此摘要是机器生成的。

这项研究引入了一种新的两阶段计算机视觉模型,用于生成各种位置的牙冠的准确深度图像. 该模型通过改善形状和表面精度来增强牙冠重建和患者治疗.

关键词:
牙科图像翻译 牙科图像翻译生成性的对抗性网络.在油漆中涂上油漆.医疗图像细分 医疗图像细分图像中的闭合深度图像.

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相关实验视频

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科学领域:

  • 计算机视觉 计算机视觉
  • 生物医学成像技术 生物医学成像技术
  • 牙科技术 牙科技术

背景情况:

  • 由于定制需求,生成牙冠的准确深度图像是具有挑战性的.
  • 现有的计算机视觉模型在流体位置的牙冠上扎.
  • 减少牙科技术人员的工作量对于有效治疗患者至关重要.

研究的目的:

  • 提出一个两阶段的计算机视觉模型,用于在不同位置生成隐形牙冠的深度图像.
  • 为了提高生成的牙冠深度图像的形状和表面结构准确度.
  • 提高计算机生成的牙冠模型的现实性和适用性.

主要方法:

  • 开发了一种结合细分和绘画网络的两阶段模型.
  • 分段网络识别了冠状位置和尺寸,以实现适应性.
  • 一个基于GAN的inpainting网络使用图像和二进制面具生成冠状表面结构.

主要成果:

  • 拟议的模型显著减少了平均平方误差 (MSE) 从0.007001降至0.002618.
  • DICE得分从0.9333提高到0.9648,这表明面具的准确性更好.
  • 与基线方法相比,该模型在生成真实的皇冠细节方面表现出卓越的性能.

结论:

  • 这种两级模型有效地生成了牙冠在不同位置的精确深度图像.
  • 细分和涂装网络的整合提高了形状和表面结构的真实性.
  • 这种方法提供了更好的现实性和直接用于患者牙科治疗的潜力.