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Automatic Labeling of Vertebral Levels Using a Robust Template-Based Approach

机译:使用基于模板的稳健方法自动标记椎骨水平

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摘要

Context. MRI of the spinal cord provides a variety of biomarkers sensitive to white matter integrity and neuronal function. Current processing methods are based on manual labeling of vertebral levels, which is time consuming and prone to user bias. Although several methods for automatic labeling have been published; they are not robust towards image contrast or towards susceptibility-related artifacts. Methods. Intervertebral disks are detected from the 3D analysis of the intensity profile along the spine. The robustness of the disk detection is improved by using a template of vertebral distance, which was generated from a training dataset. The developed method has been validated using T1- and T2-weighted contrasts in ten healthy subjects and one patient with spinal cord injury. Results. Accuracy of vertebral labeling was 100%. Mean absolute error was 2.1 ± 1.7 mm for T2-weighted images and 2.3 ± 1.6 mm for T1-weighted images. The vertebrae of the spinal cord injured patient were correctly labeled, despite the presence of artifacts caused by metallic implants. Discussion. We proposed a template-based method for robust labeling of vertebral levels along the whole spinal cord for T1- and T2-weighted contrasts. The method is freely available as part of the spinal cord toolbox.
机译:上下文。脊髓的MRI提供了对白质完整性和神经元功能敏感的多种生物标记。当前的处理方法基于椎骨水平的手动标记,这很耗时并且易于用户偏见。尽管已经发布了几种自动标记方法;它们对图像对比度或与磁化率相关的伪影不可靠。方法。从沿脊柱强度分布图的3D分析中检测出椎间盘。通过使用从训练数据集中生成的椎骨距离模板,可以提高磁盘检测的鲁棒性。使用T1和T2加权对比在十名健康受试者和一名脊髓损伤患者中验证了该开发方法。结果。椎骨标记的准确性为100%。 T2加权图像的平均绝对误差为2.1±1.7mm,T1加权图像的平均绝对误差为2.3±1.6mm。尽管存在由金属植入物引起的伪影,但已正确标记了脊髓损伤患者的椎骨。讨论。我们提出了一种基于模板的方法,可对整个T1和T2加权对比的整个脊髓进行稳健的椎骨水平标记。该方法可作为脊髓工具箱的一部分免费获得。

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