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利用哈里斯角点检测进行自动组织应变计算。

Automated Tissue Strain Calculations Using Harris Corner Detection.

机构信息

Graduate Program in Acoustics, Pennsylvania State University, 201E Applied Science Building, University Park, PA, 16802, USA.

Biomedical Engineering, Pennsylvania State University, University Park, PA, USA.

出版信息

Ann Biomed Eng. 2022 May;50(5):564-574. doi: 10.1007/s10439-022-02946-9. Epub 2022 Mar 25.

Abstract

The elastic modulus, or slope of the stress-strain curve, is an important metric for evaluating tissue functionality, particularly for load-bearing tissues such as tendon. The applied force can be tracked directly from a mechanical testing system and converted to stress using the tissue cross-sectional area; however, strain can only be calculated in post-processing by tracking tissue displacement from video collected during mechanical testing. Manual tracking of Verhoeff stain lines pre-marked on the tissue is time-consuming and highly dependent upon the user. This paper details the development and testing of an automated processing method for strain calculations using Harris corner detection. The automated and manual methods were compared in a dataset consisting of 97 rat tendons (48 Achilles tendons, 49 supraspinatus tendons), divided into ten subgroups for evaluating the effects of different therapies on tendon mechanical properties. The comparison showed that average percent differences between the approaches were 0.89% and -2.10% for Achilles and supraspinatus tendons, respectively. The automated approach reduced processing time by 83% and produced similar results to the manual method when comparing the different subgroups. This automated approach to track tissue displacements and calculate elastic modulus improves post-processing time while simultaneously minimizing user dependency.

摘要

弹性模量,即应力-应变曲线的斜率,是评估组织功能的一个重要指标,特别是对于像肌腱这样的承重组织。可以通过机械测试系统直接跟踪施加的力,并使用组织的横截面积将其转换为应力;然而,应变只能通过在机械测试过程中收集的视频来跟踪组织位移,然后在后期处理中计算。手动跟踪预先标记在组织上的 Verhoeff 染色线既耗时又高度依赖于用户。本文详细介绍了一种使用 Harris 角点检测自动计算应变的处理方法的开发和测试。在一个由 97 个大鼠肌腱(48 个跟腱,49 个冈上肌腱)组成的数据集上比较了自动和手动方法,该数据集分为十个亚组,以评估不同治疗方法对肌腱力学性能的影响。比较结果表明,对于跟腱和冈上肌腱,两种方法的平均百分比差异分别为 0.89%和-2.10%。与手动方法相比,自动方法将处理时间减少了 83%,并且在比较不同亚组时产生了相似的结果。这种自动方法可以跟踪组织位移并计算弹性模量,在提高后处理时间的同时,最大限度地减少了对用户的依赖。

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Automated Tissue Strain Calculations Using Harris Corner Detection.利用哈里斯角点检测进行自动组织应变计算。
Ann Biomed Eng. 2022 May;50(5):564-574. doi: 10.1007/s10439-022-02946-9. Epub 2022 Mar 25.

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