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从全脊柱磁共振图像中自动检测和分割椎体

Automated Vertebra Detection and Segmentation from the Whole Spine MR Images.

作者信息

Peng Zhigang, Zhong Jia, Wee William, Lee Jing-Huei

机构信息

Electr. & Comput. Eng. & Comput. Sci., Cincinnati Univ., OH.

出版信息

Conf Proc IEEE Eng Med Biol Soc. 2005;2005:2527-30. doi: 10.1109/IEMBS.2005.1616983.

Abstract

Our algorithm contains two major steps: the intervertebral disk localization step, and the vertebra detection and segmentation step. In the first step, we apply a model-based searching method to approximately locate all the intervertebral disk clues between adjacent vertebrae of the whole spine and the best slice selection. A new approach using an intensity profile on a polynomial function for fitting all these disk clues on the best slice is then used to refine the disk search process. Vertebra centers are detected, and initial boundaries are extracted in the second step. The initial test of the algorithm on the five sets of 7 sagittal slices locates all 23 intervertebral disk centers for the best slice of all five sets. For the evaluation of the boundary extraction of 22 vertebrae, our algorithm successfully locates 100%, 96.6%, 93.2%, 95.5%, 87.5% vertebra corners in image set No.1, 2, 3, 4, and 5, respectively.

摘要

我们的算法包含两个主要步骤

椎间盘定位步骤以及椎体检测与分割步骤。在第一步中,我们应用基于模型的搜索方法来大致定位整个脊柱相邻椎体之间的所有椎间盘线索以及最佳切片选择。然后使用一种新方法,即利用多项式函数上的强度轮廓来拟合最佳切片上的所有这些椎间盘线索,以优化椎间盘搜索过程。在第二步中检测椎体中心并提取初始边界。该算法在五组共7个矢状切片上的初步测试为所有五组的最佳切片定位了全部23个椎间盘中心。对于22个椎体的边界提取评估,我们的算法在图像集1、2、3、4和5中分别成功定位了100%、96.6%、93.2%、95.5%、87.5%的椎体角点。

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