统计形状模型在预测骨形状中的准确性：系统评价。
The accuracy of statistical shape models in predicting bone shape: A systematic review.
机构信息
The MSk Lab, Imperial College London, London, UK.
Department of Trauma and Orthopaedics, East Lancashire Hospitals NHS Trust, Blackburn, UK.
出版信息
Int J Med Robot. 2023 Jun;19(3):e2503. doi: 10.1002/rcs.2503. Epub 2023 Feb 10.
BACKGROUND
This systematic review aims to ascertain how accurately 3D models can be predicted from two-dimensional (2D) imaging utilising statistical shape modelling.
METHODS
A systematic search of published literature was conducted in September 2022. All papers which assessed the accuracy of 3D models predicted from 2D imaging utilising statistical shape models and which validated the models against the ground truth were eligible.
RESULTS
2127 papers were screened and a total of 34 studies were included for final data extraction. The best overall achievable accuracy was 0.45 mm (root mean square error) and 0.16 mm (average error).
CONCLUSION
Statistical shape modelling can predict detailed 3D anatomical models from minimal 2D imaging. Future studies should report the intended application domain of the model, the level of accuracy required, the underlying demographics of subjects, and the method in which accuracy was calculated, with root mean square error recommended if appropriate.
背景
本系统评价旨在确定利用统计形状建模，从二维（2D）成像准确预测三维（3D）模型的程度。
方法
2022 年 9 月进行了已发表文献的系统检索。所有评估利用统计形状模型从 2D 成像预测 3D 模型准确性并将模型与真实情况进行验证的论文均符合入选标准。
结果
共筛选出 2127 篇论文，最终有 34 项研究纳入进行数据提取。最佳整体可实现精度为 0.45 毫米（均方根误差）和 0.16 毫米（平均误差）。
结论
统计形状建模可以从最小的二维成像预测详细的 3D 解剖模型。未来的研究应报告模型的预期应用领域、所需的精度水平、受试者的基础人口统计学特征，以及准确性的计算方法，如果合适，建议使用均方根误差。
Zotero 插件