Automated quantification of COVID-19 severity and progression using chest CT images.

ABSTRACT:

Objective

To develop and test computer software to detect, quantify, and monitor progression of pneumonia associated with COVID-19 using chest CT scans.

Methods

One hundred twenty chest CT scans from subjects with lung infiltrates were used for training deep learning algorithms to segment lung regions and vessels. Seventy-two serial scans from 24 COVID-19 subjects were used to develop and test algorithms to detect and quantify the presence and progression of infiltrates associated with COVID-19. The algorithm included (1) automated lung boundary and vessel segmentation, (2) registration of the lung boundary between serial scans, (3) computerized identification of the pneumonitis regions, and (4) assessment of disease progression. Agreement between radiologist manually deline

SUBMITTER: Pu J 

PROVIDER: S-EPMC7755837 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature