Deep Learning for the Automatic Quantification of Pleural Plaques in Asbestos-Exposed Subjects.

ABSTRACT: This study aimed to develop and validate an automated artificial intelligence (AI)-driven quantification of pleural plaques in a population of retired workers previously occupationally exposed to asbestos. CT scans of former workers previously occupationally exposed to asbestos who participated in the multicenter APEXS (Asbestos PostExposure Survey) study were collected retrospectively between 2010 and 2017 during the second and the third rounds of the survey. A hundred and forty-one participants with pleural plaques identified by expert radiologists at the 2nd and the 3rd CT screenings were included. Maximum Intensity Projection (MIP) with 5 mm thickness was used to reduce the number of CT slices for manual delineation. A Deep Learning AI algorithm using 2D-convolutional neural networks w

SUBMITTER: Benlala I 

PROVIDER: S-EPMC8835296 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature