深度学习对CBCT在牙科中的应用
Wenjie Fan1,2, Jiaqi Zhang1,2, Nan Wang1,2
1Department of Stomatology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
Diagnostics (Basel, Switzerland)
|June 28, 2023
概括
深度学习 (DL) 显著增强了牙圆束计算机断层扫描 (CBCT) 分析,提高了诊断和细分等任务的准确性和效率. 虽然有希望,但需要进一步的研究和伦理考虑才能广泛采用临床.
科学领域:
- 牙科 牙科是指牙科的专业.
- 放射学 放射学是一门学科.
- 人工智能的人工智能
背景情况:
- 圆束计算机断层扫描 (CBCT) 在牙科中对于分析牙和周围组织至关重要.
- 手动CBCT分析耗时且依赖于用户.
- 深度学习 (DL) 为提高CBCT分析效率和准确性提供了潜在的解决方案.
研究的目的:
- 为牙科CBCT分析提供当前深度学习应用的概述.
- 突出这一领域的DL的潜在和未来研究方向.
主要方法:
- 从主要科学数据库 (PubMed,IEEE,谷歌学者,科学网) 系统审查研究文章,截至2022年12月.
- 专注于将深度学习模型应用于牙科中CBCT图像的研究.
主要成果:
- 深度学习模型在牙科CBCT分析方面取得了显著进展,在许多放射学图像分析任务中实现了临床医生级准确性.
- 应用包括自动诊断,细分,解剖结构 (牙,神经,骨,呼吸道) 的分类和手术前规划.
- 准确性需要在某些领域进行改进;道德问题和设备的变化带来了挑战.
结论:
- 深度学习与CBCT相结合显示出极大的潜力,可以减少牙科图像阅读工作量,并作为临床决策辅助工具.
- 需要进一步的研究来解决局限性问题,并促进更广泛的临床实施.
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