Fig 1.
The top row shows the radiological signs on frontal chest radiographs. The left frontal chest radiograph shows the flattening of the diaphragm, and the right shows irregular radiolucency. The bottom two chest radiographs show the radiological signs on the lateral chest radiograph. The left lateral chest radiograph clearly shows the flattening of the diaphragmatic contours while the right demonstrates an abnormal retrosternal space.
Table 1.
The four signs of emphysema as described by Sutinen et al. [18].
Fig 2.
Data acquisition diagram.
Fig 3.
Illustration of how the emphysema score is created from the sign models.
For each view, we train a separate model predicting the two relevant sign probabilities. In the end, we average these probabilities to calculate a combined emphysema score. The indicated scores are calculated using the CXRs shown in the figure for this specific subject.
Fig 4.
Illustration of the black-box model.
For each view, we define a model with 512 outputs. The outputs from the two models are concatenated and the probability of emphysema is predicted from this final layer. The indicated score is calculated using the CXRs shown in the figure for this specific subject.
Table 2.
Patient statistics of the dataset of 3,000 initially selected studies.
Table 3.
Annotation results for the training and test datasets.
Table 4.
Inter-observer variability.
Table 5.
Comparison of the radiologists and the models.
Fig 5.
ROC curve comparison of the combined emphysema signs model for detecting emphysema with at least 2 signs, the black-box emphysema model, and a radiologists sensitivity specificity point.
ROC curves are drawn for 2 different reference standards. R1 as reference standard (left)and R2 as reference standard (centre), and finally for only those cases where the radiologists agreed on the emphysema label (right). The 95% confidence intervals and error bars are calculated by bootstrapping.