老板:骨头,器官和皮肤的形状模型
Karthik Shetty1, Annette Birkhold2, Srikrishna Jaganathan1
1Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, 91058, Germany; Siemens Healthcare GmbH, Forchheim, 91301, Germany.
Computers in biology and medicine
|September 1, 2023
概括
这项研究引入了一种新的可变形的人体形状和姿势模型,将CT扫描中的皮肤,器官和骨整合起来. 这种先进的解剖模型提高了医学成像和图像引导干预的准确性.
科学领域:
- 医学成像医学成像
- 计算解剖学的计算解剖学
- 生物医学工程 生物医学工程
背景情况:
- 虚拟解剖模型增强了临床任务,如工作流程自动化和图像引导干预.
- 当前的统计形状模型 (SSM) 往往缺乏全面的器官/骨代表性和人口多样性.
- 高质量的患者表面和内部器官数据对于准确的姿势和形状估计至关重要.
研究的目的:
- 开发一个可变形的人类形状和姿势模型,整合皮肤,内脏和骨.
- 为了改善医疗应用,创建一个整体的解剖学表示.
- 解决现有SSM在人口代表性和范围方面的局限性.
主要方法:
- 从CT图像中学习了一个可变形的模型,结合了皮肤,器官和骨.
- 概率PCA在姿势正常化空间中使用,以建模统计变异,同时保持关节动力学.
- 在注册和公开可用的数据集上评估模型性能.
主要成果:
- 该模型在注册数据集上实现了骨头平均误差3.6毫米,器官平均误差8.8毫米.
- 使用皮肤表面数据或患者元数据导致骨器官错误总值分别为8.68毫米和8.11毫米.
- 在TotalSegmentator数据集上的错误为骨头的5.10毫米,器官的8.72毫米.
结论:
- 可以准确高效地创建解剖学参数化的统计形状模型.
- 拟议的整体模型为各种医疗应用中的自动化提供了显著的好处.
- 该模型允许构建可直接集成到各种医疗应用中的形状模型.
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