论文标题
通过深度学习，肌肉骨骼X光片中自动化异常检测
Automating Abnormality Detection in Musculoskeletal Radiographs through Deep Learning
论文作者
论文摘要
本文介绍了Murad（肌肉骨骼X光异常检测工具），该工具可以帮助放射科医生自动检测肌肉骨骼X光片（骨X射线）的异常。 Murad利用卷积神经网络（CNN）可以准确预测骨X射线是否异常，并利用类激活图（CAM）来定位图像中的异常。 Murad的F1得分为0.822，Cohen的Kappa为0.699，这与专家放射科医生的表现相当。
This paper introduces MuRAD (Musculoskeletal Radiograph Abnormality Detection tool), a tool that can help radiologists automate the detection of abnormalities in musculoskeletal radiographs (bone X-rays). MuRAD utilizes a Convolutional Neural Network (CNN) that can accurately predict whether a bone X-ray is abnormal, and leverages Class Activation Map (CAM) to localize the abnormality in the image. MuRAD achieves an F1 score of 0.822 and a Cohen's kappa of 0.699, which is comparable to the performance of expert radiologists.
