Enhancing pectus excavatum diagnosis with an automated batch evaluation tool for chest computed tomography images.

ABSTRACT: We aimed to implement a fully automatic computed tomography (CT) image-detection programming algorithm as a pectus excavatum (PE) diagnostic tool, facilitating comprehensive chest wall deformity evaluation. We developed our algorithm using MATLAB, leveraging the Hounsfield unit threshold and region growing methods. The MATLAB graphical user interface enables the direct use of our program. We validated the model using CT images of anthropomorphic phantoms and one normal individual. The measurement values obtained by our algorithm demonstrated very small differences compared to the known anthropomorphic phantom model data and manual measurement. For algorithm testing, 17,214 chest CT scans obtained from 57 PE patients were processed by the algorithm and independently reviewed by a radiologis

SUBMITTER: Fan YJ 

PROVIDER: S-EPMC11461728 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature