论文标题
使用深度学习方法的自动化心胸比计算和心脏肿大检测
Automated Cardiothoracic Ratio Calculation and Cardiomegaly Detection using Deep Learning Approach
论文作者
论文摘要
我们提出了一种用于计算胸部X射线膜的心胸比（CTR）的算法。我们的方法采用了基于U-NET的深度学习模型，该模型用VGG16编码器从胸部X射线图像中提取肺和心脏面具，并从获得的掩码的范围中计算CTR。人类放射科医生评估了我们的CTR测量结果，并接受了76.5美元的$ $ $ $，而无需进行调整，将其包括在医疗报告中。该结果转化为使用我们的自动化工具为放射科医生节省的大量时间和人工。
We propose an algorithm for calculating the cardiothoracic ratio (CTR) from chest X-ray films. Our approach applies a deep learning model based on U-Net with VGG16 encoder to extract lung and heart masks from chest X-ray images and calculate CTR from the extents of obtained masks. Human radiologists evaluated our CTR measurements, and $76.5\%$ were accepted to be included in medical reports without any need for adjustment. This result translates to a large amount of time and labor saved for radiologists using our automated tools.
