一种基于极大特征点的三维椎骨分割方法

椎骨的精确分割对于椎骨形态学研究和脊柱疾病的诊断和治疗有重要意义。通过 对正常人脊柱 CT 图序列的变化规律进行研究，提出了一种基于 CT 图像序列并利用椎骨面积 变化规律进行分割的椎骨分割算法。该方法通过对预先处理后的 CT 图像序列进行椎骨区域面 积统计，找出用于分割的显著极大特征点，并利用连续图像相似性筛选出椎骨实际分割点，最 后从序列中提取图像并进行三维重建。实验表明，该算法对正常人体腰椎和胸椎下部的椎骨 CT 图像序列有良好地分割效果，自动化程度较高。对脊柱形态学研究和矫正手术模拟有重要意义。 

A Method of 3D Vertebra Segmentation Based on Maximum Feature

Accurate segmentation of vertebrae has become more and more important for the diagnosis and treatment of spinal diseases. After studying the change rule of some spinal CT image sequences of normal people, we proposed a new vertebral segmentation algorithm based on vertebral area change regulation. This method first calculates the area of vertebral region in the image after pre-processing, then finds out the significant features for segmentation, uses image similarity of continuous images to select the actual segmentation points, and finally extracts vertebral images from image sequence for 3D reconstruction. The innovation of the method is that a new segmentation algorithm based on the maximum feature and correlation of CT image sequence is proposed. The experimental results show that the algorithm has a good segmentation effect on the CT image sequence of lumbar vertebrae and the lower thoracic vertebrae of normal human bodies and it has a high degree of automation. This study is of great significance to the morphological study of the spine and the simulation of the scoliosis operation.