对比三款工具在腹部MRI多器官分割的性能，发现MRSeg表现最佳。
Benchmarking Multi-Organ Segmentation Tools for Multi-Parametric T1-weighted Abdominal MRI
- 基于杜克肝数据集，测试三种开源分割工具在四类T1加权序列上的表现。
- MRSeg平均Dice达80.7，显著优于另外两个工具（p<0.05）。
- 适合放射科研究者评估MRI分割工具在临床序列中的适用性。
多参数MRI中多器官分割对放射学应用至关重要，例如将影像生物标志物与疾病状态（如肝硬化、糖尿病）关联。近期有三款公开工具——MRSegmentator（MRSeg）、TotalSegmentator MRI（TS）和TotalVibeSegmentator（VIBE）被提出用于MRI多器官分割。然而，这些工具在特定MRI序列上的表现尚未量化。本研究从公开的杜克肝数据集选取40个体积，包含每类预增强脂肪抑制T1、动脉期T1w、门静脉期T1w和延迟期T1w各10个体积，共10个腹部结构经人工标注。在此定制数据集上对三款工具进行基准测试。结果表明，MRSeg获得80.7±18.6的Dice分数和8.9±10.4 mm的豪斯多夫距离（HD）误差，在不同序列类型中表现最优（p<0.05），显著优于TS和VIBE。
原文摘要 · Abstract (English)
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.
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