Automated detection and segmentation of non-small cell lung cancer computed tomography images.
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ABSTRACT:
SUBMITTER: Primakov SP
PROVIDER: S-EPMC9198097 | biostudies-literature | 2022 Jun
REPOSITORIES: biostudies-literature
Publications
Automated detection and segmentation of non-small cell lung cancer computed tomography images.
Primakov Sergey P SP Ibrahim Abdalla A van Timmeren Janita E JE Wu Guangyao G Keek Simon A SA Beuque Manon M Granzier Renée W Y RWY Lavrova Elizaveta E Scrivener Madeleine M Sanduleanu Sebastian S Kayan Esma E Halilaj Iva I Lenaers Anouk A Wu Jianlin J Monshouwer René R Geets Xavier X Gietema Hester A HA Hendriks Lizza E L LEL Morin Olivier O Jochems Arthur A Woodruff Henry C HC Lambin Philippe P
Nature communications 20220614 1
Detection and segmentation of abnormalities on medical images is highly important for patient management including diagnosis, radiotherapy, response evaluation, as well as for quantitative image research. We present a fully automated pipeline for the detection and volumetric segmentation of non-small cell lung cancer (NSCLC) developed and validated on 1328 thoracic CT scans from 8 institutions. Along with quantitative performance detailed by image slice thickness, tumor size, image interpretatio ...[more]
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