Longitudinal Assessment of COVID-19 Using a Deep Learning-based Quantitative CT Pipeline: Illustration of Two Cases.

Figure 1: Evolution of COVID-19 in a 48-year-old woman across 16 days of treatment. A, Axial unenhanced chest CT images at four time points (dates annotated in each panel) show peripheral ground-glass opacities and consolidation. B, Color overlay of voxel-level segmentation at the same level and time points as in A show pulmonary opacities displayed in yellow and normal lung in blue. C, Coronal reconstructions at the same time points as in A show progressive improvement of the lung opacities. D, Three-dimensional volume-rendered reconstructions at the same time points as in A show pulmonary opacities displayed in yellow, normal lung and vessels in light gray, and tracheobronchial tree in green. The volumetric assessment of the pulmonary opacities derived from the deep learning–based quantitative CT analysis is annotated at different time points on the volume-rendered images. LOV= lung …