Fig. 1

Schematic of the proposed pipeline. The different steps of the pipeline are denoted with letter from A–I. Overall pipeline of CXR framework for scoring opacity using deep learning. Steps include (A) Data Preparation: DICOM to PNG conversion and application of exclusion criteria; (B) image preprocessing and ROI extraction; (C) train/test data split and data balancing; (D) transfer learning setup for testing models generated using multiple combinations of X-ray segmentation schemes, sampling schemes to overcome dataset bias, and CNN architectures; (E) level 1 – single-fold analysis to determine top ‘N’ models; (F) level 2 – K-fold cross validation to determine best model; (G) comparison of best model with reader scores; (H) heatmap for visualization; and (I) model performance analysis across different patient populations, grouped by sex, race, and COVID-19 status