Quantitative Vertebral Morphometry Using Neighbor-Conditional Shape Models
Quantitative Vertebral Morphometry Using Neighbor-Conditional Shape Models
复制标题
使用邻近条件形状模型进行定量椎骨形态测量
DOI：
10.1007/11866565_1
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发表时间：
2006
期刊：
影响因子：
--
通讯作者：
M. Nielsen
中科院分区：
文献类型：
--
作者：
Marleen de Bruijne;Michael T. Lund;L. Tankó;P. Pettersen;M. Nielsen
提出了一种新的从X线图像中定量脊椎骨折的方法。使用在一组健康脊柱上训练的成对条件形状模型，最可能的正常椎骨形状是以图像中的所有其他椎骨为条件来估计的。真实形状和重建的正常形状之间的差异随后被用作异常的量度。与目前的（半）定量分级策略相比，该方法考虑到了完整的形状，它使用了患者特定的参考结合人口为基础的信息，生物学变化的椎骨形状和椎骨的相互关系，它提供了一个连续的措施modelity.The方法是证明在212侧位脊柱X线片，共78骨折。预测和真实形状之间的距离对于未骨折的椎骨为1.0 mm，对于骨折为3.7 mm，这使得诊断和评估骨折的严重程度成为可能。
A novel method for vertebral fracture quantification from X-ray images is presented. Using pairwise conditional shape models trained on a set of healthy spines, the most likely normal vertebra shapes are estimated conditional on all other vertebrae in the image. The differences between the true shape and the reconstructed normal shape is subsequently used as a measure of abnormality. In contrast with the current (semi-)quantitative grading strategies this method takes the full shape into account, it uses a patient-specific reference by combining population-based information on biological variation in vertebra shape and vertebra interrelations, and it provides a continuous measure of deformity.The method is demonstrated on 212 lateral spine radiographs with in total 78 fractures. The distance between prediction and true shape is 1.0 mm for unfractured vertebrae and 3.7 mm for fractures, which makes it possible to diagnose and assess the severity of a fracture.
影响因子：
4
作者：
Ismail, AA;Cooper, C;O'Neill, TW
通讯作者：
O'Neill, TW