人工智能
计算机科学
深度学习
目标检测
计算机视觉
计算机断层摄影术
模式识别(心理学)
放射科
医学
作者
Kritsasith Warin,Sothana Vicharueang,Patcharapon Jantana,Wasit Limprasert,Bhornsawan Thanathornwong,Siriwan Suebnukarn
出处
期刊:Studies in health technology and informatics
日期:2024-01-25
摘要
This study deploys the deep learning-based object detection algorithms to detect midfacial fractures in computed tomography (CT) images. The object detection models were created using faster R-CNN and RetinaNet from 2,000 CT images. The best detection model, faster R-CNN, yielded an average precision of 0.79 and an area under the curve (AUC) of 0.80. In conclusion, faster R-CNN model has good potential for detecting midfacial fractures in CT images.
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