Pedicle screw (PS) implantation is an ideal method for the treatment of severe multilevel vertebral instability. The key problem is the accuracy of PS fixation. In this paper, the spectrum of different tissues along the fixation trajectory of PS is studied to tackle the accuracy problem. Fresh porcine vertebrae, bovine vertebrae, and ovine vertebrae were measured by using the near-infrared spectrum (NIRs) device to obtain the reflected spectrum from these vertebrae. Along the fixation trajectory of PS, the classification method based on the sparse representation-based classifier (SRC) was applied to different vertebral tissues (cortical bones and cancellous bones). Considering the large amount of spectral data, sparse preserving projection (SPP) was applied to improve the performance of SRC. The proposed method based on the SPP method for dimensionality reduction and the SRC method for tissue recognition was first used in vertebrae classification and showed superior performance compared with other classification methods, such as SVM and 1NN. The results gained from this project are vital significant to the development of hi-tech medical instruments with independent intellectual property rights.

中文翻译：

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椎弓根螺钉固定轨迹对不同动物椎体分类的稀疏表示

椎弓根螺钉（PS）植入是治疗严重的多级脊椎不稳的理想方法。关键问题是PS固定的准确性。本文研究了沿PS固定轨迹的不同组织的光谱，以解决精度问题。通过使用近红外光谱（NIR）设备测量新鲜的猪椎骨，牛椎骨和羊椎骨，以获得这些椎骨的反射光谱。沿着PS的固定轨迹，将基于稀疏表示的分类器（SRC）的分类方法应用于不同的椎骨组织（皮质骨和松质骨）。考虑到大量的光谱数据，稀疏保留投影（SPP）被用来提高SRC的性能。提出的基于SPP方法的降维方法和基于SRC的组织识别方法在椎骨分类中首次使用，与其他分类方法（例如SVM和1NN）相比，其性能更高。从该项目获得的结果对于开发具有自主知识产权的高科技医疗仪器至关重要。