基于CT的手动,半自动和自动方法对肝脏体积细分的比较
Berna Dogan1, Sadik Bugrahan Simsek1, Sefa Sonmez1
1Department of Anatomy, Faculty of Medicine, Tokat Gaziosmanpasa University, Tokat 60100, Türkiye.
Diagnostics (Basel, Switzerland)
|March 14, 2026
概括
半自动和自动CT肝脏细分方法为手动细分提供了有效的替代方案,保持临床体积一致. TotalSegmentator显示了最接近的协议,使其适用于例行肝体积测量.
科学领域:
- 医疗成像医学成像
- 放射学 放射学是一门学科.
- 计算解剖学的计算解剖学
背景情况:
- 准确的肝体积测量对于临床决策至关重要.
- 手动细分是耗时的,容易变化.
- 自动化方法旨在提高效率和一致性.
研究的目的:
- 为了比较半自动和自动CT肝脏细分方法与手动细分.
- 为了评估体积一致性和处理效率.
- 确定用于常规临床实践的最佳方法.
主要方法:
- 从86个人的CT图像进行了回顾性分析.
- 手动细分肝脏体积,并使用RVX半自动,RVX深度学习和TotalSegmentator进行细分.
- 统计分析包括ANOVA,布兰德-阿尔特曼分析,子相似系数 (DICE) 和豪斯多夫距离 (HD).
主要成果:
- RVX深度学习显示了显著更高的体积 (p < 0.001);其他人没有显著的差异.
- 总分段器和RVX半自动显示了与手动分段的高体积一致性.
- RVX深度学习最快,手动细分最慢;所有自动化方法的DICE分数都很高.
结论:
- 半自动和自动的肝脏细分大大减少了处理时间.
- TotalSegmentator为例行CT肝体积计提供了与手动细分最接近的协议.
- 深度学习方法更快,但可能会高估体积,影响精度敏感的应用程序.
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