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腰椎间盘的形态和组成:手动测量和计算机辅助算法的比较分析

Yiting Cheng¹, Yuyan Ma², Kang Li³

¹School of Mechanical Engineering, Sichuan University, Chengdu 610000, China.

Bioengineering (Basel, Switzerland)

|May 25, 2024

概括

计算机辅助方法准确地测量腰椎间盘 (IVD) 中的核与横截面积 (NP-to-CSA) 比率,为脊椎的生物力学模型提供了宝贵的数据.

科学领域:

生物医学工程生物医学工程
脊柱生物力学脊柱生物力学
医学成像分析医学成像分析

背景情况:

腰椎间盘 (IVD) 的核与横截面积 (NP-to-CSA) 比率对于脊柱生物力学的有限元模型 (FEM) 至关重要.
从历史上看,准确测量这种比率一直是具有挑战性的,而且报告不足.

研究的目的:

为了比较手动与计算机辅助方法的准确性和可靠性,用于确定腰部IVD中的NP-CSA比率.
调查性别和脊柱水平对这一比例的影响.

主要方法:

使用了123名受试者的匿名MRI扫描 (400个腰部IVD).
测量由脊椎外科医生手动进行,并使用模糊的C-means (FCM) 和区域增长 (RG) 分段算法.
通过手动和计算机辅助方法比较结果,分析性别和脊柱水平的影响.

主要成果:

手动测量结果显示,NP与CSA的比率为46%.
计算机辅助方法 (FCM和RG) 的比率分别为39%和38%.
手动推导的比率明显大于计算机辅助技术的比率.

结论:

计算机辅助细分算法 (FCM,RG) 为评估内部磁盘组成提供可靠的结果.
与传统的手动测量相比,这些方法提供了更容易使用的方法.
脊柱生物力学的有限元模型应该考虑到NP-CSA比率的观察到的变化.

关键词:

计算机辅助细分是指计算机辅助的细分.截面面积的横截面积是什么有限元素建模有限元素建模模糊的C意味着C.椎间盘之间的椎间盘.腰部脊柱腰部脊柱腰部脊柱它的核是脉冲的脉冲.增长地区增长地区增长地区.

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