Automatic measurement of cardiothoracic ratio in chest x-ray images with ProGAN-generated dataset, ACI
The paper developed a solution containing three steps on lung and heart segmentation, CTR calculation and cardiomegaly classification. The segmentation models were trained and validated on the publicly available datasets with the mask groundtruth, based on U-Net architecture. The models were then used for segmenting areas of the lungs and heart in chest x-ray images on unseen datasets, including the self-collected dataset and the new dataset generated by ProGAN.
The segmented areas were used to compute CTR values which were then used to identify the cardiomegaly by comparing with the cut-off threshold. It reported an average error of 3.08% for the CTR calculation on the self-collected dataset. Also, it reported the accuracy of 94.61%, the sensitivity of 88.31%, and the specificity of 94.20% for cardiomegaly classification on the dataset constructed by ProGAN.