Robustness of radiomics to variations in segmentation methods in multimodal brain MRI.

ABSTRACT: Radiomics in neuroimaging uses fully automatic segmentation to delineate the anatomical areas for which radiomic features are computed. However, differences among these segmentation methods affect radiomic features to an unknown extent. A scan-rescan dataset (n = 46) of T1-weighted and diffusion tensor images was used. Subjects were split into a sleep-deprivation and a control group. Scans were segmented using four segmentation methods from which radiomic features were computed. First, we measured segmentation agreement using the Dice-coefficient. Second, robustness and reproducibility of radiomic features were measured using the intraclass correlation coefficient (ICC). Last, difference in predictive power was assessed using the Friedman-test on performance in a radiomics-based sleep depr

SUBMITTER: Poirot MG 

PROVIDER: S-EPMC9537186 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature