Automated segmentation of the fractured vertebrae on CT and its applicability in a radiomics model to predict fracture malignancy.

ABSTRACT: Although CT radiomics has shown promising results in the evaluation of vertebral fractures, the need for manual segmentation of fractured vertebrae limited the routine clinical implementation of radiomics. Therefore, automated segmentation of fractured vertebrae is needed for successful clinical use of radiomics. In this study, we aimed to develop and validate an automated algorithm for segmentation of fractured vertebral bodies on CT, and to evaluate the applicability of the algorithm in a radiomics prediction model to differentiate benign and malignant fractures. A convolutional neural network was trained to perform automated segmentation of fractured vertebral bodies using 341 vertebrae with benign or malignant fractures from 158 patients, and was validated on independent test sets (int

SUBMITTER: Park T 

PROVIDER: S-EPMC9038736 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature