Comparison of automated subcortical segmentation methods: VolBrain vs. 3D Slicer in brain volumetry

Objective:Accurate volume measurements of subcortical brain structures are essential in neuroimaging studies. This study aimed to compare two automated segmentation algorithms, 3D Slicer and VolBrain, for subcortical brain volumetry. Method:Subcortical volume measurements obtained using 3D Slicer and VolBrain were compared using the Neurofeedback Skull-stripped (NFBS) dataset. Statistical analyses included the coefficient of determination (R2) and Bland-Altman (B-A) plots. Volumetric measurements from both tools were evaluated across multiple subcortical brain regions. Results:Strong agreement was observed for the caudate nucleus, thalamus, and hippocampus, while notable discrepancies were identified in the amygdala, globus pallidus, and nucleus accumbens. Both constant and proportional systematic errors were detected in certain regions, with greater variability observed in 3D Slicer measurements. Intraclass Correlation Coefficient (ICC) analysis demonstrated weak agreement for the accumbens and amygdala, and moderate agreement for the hippocampus and thalamus, highlighting region-specific differences in performance Conclusion:Both VolBrain and 3D Slicer are effective tools for subcortical brain volumetry. VolBrain provides a fully automated workflow, whereas 3D Slicer allows greater flexibility through detailed corrections. Method selection should be guided by research objectives, regions of interest, and image quality. Further validation across diverse datasets is warranted to improve clinical applicability, particularly in regions showing lower agreement.