Deep learning-based cardiothoracic ratio measurement on chest radiograph: accuracy improvement without self-annotation.

Deep learning-based cardiothoracic ratio estimation on chest radiographs correlated favorably with the results obtained through manual measurements by radiologists. When the model was trained on additional local images generated by the initial model, the correlation with manual measurement improved even more than the initial model alone.