Fig. 3.

Automatic segmentation of both lungs with quantitative extraction of well-aerated parenchyma, ground glass opacities, semi-consolidation and consolidation. This figure reports the coronal images (on top) and the corresponding 3D volume rendering (bottom), obtained during post-processing performed using a dedicated software (IntelliSpace Portal v.8.0, Philips Medical Systems, Eindhoven, The Netherlands). The software performs a fully automatic segmentation of both lungs from native CT dataset (A). After visual check and manual correction of any segmentation error, the HU thresholds calculated as in Fig. 2 were applied in a multistep fashion analysis. In the first step (B) consolidation pattern was extracted from total lung volume applying the threshold -290HU. In the second step (C) consolidation plus semi-consolidation were extracted from total lung volume applying the threshold -570HU. In the final step (D) consolidation, semi-consolidation and ground glass opacities were extracted from total lung volume applying the threshold -780HU and the red volume (D) represent the well-aerated parenchyma. Hence, consolidation volume was obtained subtracting red volume in B from total lung volume (A); semi-consolidation volume was obtained subtracting red volume in C from red volume in B; ground glass volume was obtained subtracting red volume in D from red volume in C. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)