Yates Keegan M, Untaroiu Costin D
Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA 24060, USA.
Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA 24060, USA.
J Biomech. 2018 Jun 6;74:50-56. doi: 10.1016/j.jbiomech.2018.04.016. Epub 2018 Apr 16.
Statistical shape analysis was conducted on 15 pairs (left and right) of human kidneys. It was shown that the left and right kidney were significantly different in size and shape. In addition, several common modes of kidney variation were identified using statistical shape analysis. Semi-automatic mesh morphing techniques have been developed to efficiently create subject specific meshes from a template mesh with a similar geometry. Subject specific meshes as well as probabilistic kidney meshes were created from a template mesh. Mesh quality remained about the same as the template mesh while only taking a fraction of the time to create the mesh from scratch or morph with manually identified landmarks. This technique can help enhance the quality of information gathered from experimental testing with subject specific meshes as well as help to more efficiently predict injury by creating models with the mean shape as well as models at the extremes for each principal component.
对15对（左右）人类肾脏进行了统计形状分析。结果表明，左右肾脏在大小和形状上存在显著差异。此外，使用统计形状分析确定了几种常见的肾脏变异模式。已经开发了半自动网格变形技术，以有效地从具有相似几何形状的模板网格创建特定于个体的网格。从模板网格创建了特定于个体的网格以及概率性肾脏网格。网格质量与模板网格大致相同，而从零开始创建网格或使用手动识别的地标进行变形只需要花费一小部分时间。该技术有助于提高从使用特定于个体的网格进行的实验测试中收集的信息质量，并且通过创建具有平均形状以及每个主成分极端情况的模型，有助于更有效地预测损伤。
