The COVID-19 Lung Segmentation project provides a novel, unsupervised and fully auto- mated pipeline for the semantic segmentation of ground-glass opacity (GGO) areas in chest Computer Tomography (CT) scans of patients affected by COVID-19. In the project we provide a series of scripts and functions for the automated segmentation of lungs 3D areas, segmentation of GGO areas, and estimation of radiomic features.
COVID-19 Lung Segmentation / Biondi, Riccardo; Curti, Nico; Giampieri, Enrico; Castellani, Gastone. - In: JOURNAL OF OPEN SOURCE SOFTWARE. - ISSN 2475-9066. - ELETTRONICO. - 6:65(2021), pp. 3447.1-3447.3. [10.21105/joss.03447]
COVID-19 Lung Segmentation
Biondi, Riccardo;Curti, Nico;Giampieri, Enrico;Castellani, Gastone
2021
Abstract
The COVID-19 Lung Segmentation project provides a novel, unsupervised and fully auto- mated pipeline for the semantic segmentation of ground-glass opacity (GGO) areas in chest Computer Tomography (CT) scans of patients affected by COVID-19. In the project we provide a series of scripts and functions for the automated segmentation of lungs 3D areas, segmentation of GGO areas, and estimation of radiomic features.| File | Dimensione | Formato | |
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