一种基于YOLOv12的方法,用于自动检测2D侧头骨X射线图像上的头脑测量标志
Parth Dhananjay Akre1, Yash Ganesh Ghavghave2, Utkarsha Pacharaney3
1Department of Artificial Intelligence and Data Science, Faculty of Engineering and Technology, Datta Meghe Institute of Higher Education and Research (Deemed to Be University), Wardha, Maharashtra, 442001, India. parthakre119@gmail.com.
这项研究介绍了一种使用YOLOv12进行自动头脑测量地标检测的AI管道. 该方法显著缩短了时间,并提高了正牙分析的准确性.
科学领域:
- 矯正牙科 矯正牙科是一種矯正牙科.
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 脑仪分析对于正牙诊断和治疗规划至关重要.
- 手动地标识别是耗时的,容易变化.
- 人工智能 (AI) 为医学图像分析提供了潜在的解决方案.
研究的目的:
- 开发一个自动化管道用于使用人工智能的头测量地标检测.
- 为了提高头计分析在正牙科的效率和准确性.
主要方法:
- 实现一个自动地标检测管道,使用YOLOv12.
- 在公开可用的脑力测量数据集上进行培训和评估.
主要成果:
- YOLOv12模型在地标定位方面实现了高精度.
- 53.47%的地标位于1毫米范围内,80.57%位于2毫米范围内.
结论:
- 拟议的基于YOLOv12的管道提供了一个高效和准确的解决方案,用于脑测量地标检测.
- 这种人工智能方法有可能提高正牙诊断和治疗规划.
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