Benchmarking Multi-Organ Segmentation Tools for Multi-Parametric T1-weighted Abdominal MRI
Journal:
arXiv
Published Date:
Apr 10, 2025
Abstract
The segmentation of multiple organs in multi-parametric MRI studies is
critical for many applications in radiology, such as correlating imaging
biomarkers with disease status (e.g., cirrhosis, diabetes). Recently, three
publicly available tools, such as MRSegmentator (MRSeg), TotalSegmentator MRI
(TS), and TotalVibeSegmentator (VIBE), have been proposed for multi-organ
segmentation in MRI. However, the performance of these tools on specific MRI
sequence types has not yet been quantified. In this work, a subset of 40
volumes from the public Duke Liver Dataset was curated. The curated dataset
contained 10 volumes each from the pre-contrast fat saturated T1, arterial T1w,
venous T1w, and delayed T1w phases, respectively. Ten abdominal structures were
manually annotated in these volumes. Next, the performance of the three public
tools was benchmarked on this curated dataset. The results indicated that MRSeg
obtained a Dice score of 80.7 $\pm$ 18.6 and Hausdorff Distance (HD) error of
8.9 $\pm$ 10.4 mm. It fared the best ($p < .05$) across the different sequence
types in contrast to TS and VIBE.
