Spinal ligaments are crucial elements in the complex biomechanical simulation models as they transfer forces on the bony structure, guide and limit movements and stabilize the spine. The spinal ligaments encompass seven major groups being responsible for maintaining functional interrelationships among the other spinal components. Determination of the ligament origin and insertion points on the 3D vertebrae models is an essential step in building accurate and complex spine biomechanical models. In our paper, we propose a pipeline that is able to detect 66 spinal ligament attachment points by using a step-wise approach. Our method incorporates a fast vertebra registration that strategically extracts only 15 3D points to compute the transformation, and edge detection for a precise projection of the registered ligaments onto any given patient-specific vertebra model. Our method shows high accuracy, particularly in identifying landmarks on the anterior part of the vertebra with an average distance of 2.24 mm for anterior longitudinal ligament and 1.26 mm for posterior longitudinal ligament landmarks. The landmark detection requires approximately 3.0 seconds per vertebra, providing a substantial improvement over existing methods. Clinical relevance: using the proposed method, the required landmarks that represent origin and insertion points for forces in the biomechanical spine models can be localized automatically in an accurate and time-efficient manner.

翻译：脊柱韧带作为复杂生物力学仿真模型中的关键要素，通过向骨性结构传递力、引导并限制运动以及维持脊柱稳定性发挥重要作用。脊柱韧带包含七个主要群组，负责维持脊柱各组件间的功能关联性。在三维椎体模型上确定韧带起止点是构建精确复杂脊柱生物力学模型的关键步骤。本文提出一种分步式处理流程，能够检测66个脊柱韧带附着点。该方法采用快速椎体配准技术，通过策略性提取仅15个三维点来计算变换矩阵，并结合边缘检测实现已配准韧带在任意患者特异性椎体模型上的精确投影。本方法展现出较高的定位精度，尤其在椎体前部标志点识别方面表现突出：前纵韧带标志点的平均距离误差为2.24毫米，后纵韧带标志点误差为1.26毫米。单椎体标志点检测耗时约3.0秒，较现有方法有显著提升。临床意义：采用本方法可自动、精准且高效地定位生物力学脊柱模型中表征力作用起止点的关键标志点。