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Automatic Vertebral Column Extraction by Whole-Body Bone SPECT Scan

机译:通过全身骨骼SPECT扫描自动提取椎骨柱

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摘要

Bone extraction and division can enhance the accuracy of diagnoses based on whole-body bone SPECT data. This study developed a method for using conventional SPECT for automatic recognition of the vertebral column. A novel feature of the proposed approach is a novel “bone graph" image description method that represents the connectivity between these image regions to facilitate manipulation of morphological relationships in the skeleton before surgery. By tracking the paths shown on the bone graph, skeletal structures can be identified by performing morphological operations. The performance of the method was evaluated quantitatively and qualitatively by two experienced nuclear medicine physicians. Datasets for whole-body bone SPECT scans in 46 lung cancer patients with bone metastasis were obtained with Tc-99m MDP. The algorithm successfully segmented vertebrae in the thoracolumbar spine. The quantitative assessment shows that the segmentation method achieved an average TP, FP, and FN rates of 95.1%, 9.1%, and 4.9%. The qualitative evaluation shows an average acceptance rate of 83%, where the data for the acceptable and unacceptable groups had a Cronbach's alpha value of 0.718, which indicated reasonable internal consistency and reliability.
机译:骨骼提取和分割可以提高基于全身骨骼SPECT数据的诊断准确性。这项研究开发了一种使用常规SPECT进行脊柱自动识别的方法。所提出方法的新颖特征是新颖的“骨图”图像描述方法,该方法表示这些图像区域之间的连通性,以利于在手术前操纵骨骼中的形态关系。通过跟踪骨骼图上显示的路径,骨骼结构可以通过进行形态学操作来鉴定该方法的性能,由两名经验丰富的核医学医师进行定量和定性评估,并使用Tc-99m MDP获得46例肺癌骨转移患者全身SPECT扫描的数据集。胸腰椎成功地分割椎骨,定量评估表明,该分割方法的平均TP,FP和FN率分别为95.1%,9.1%和4.9%,定性评估显示平均接受率为83%,其中可接受组和不可接受组的数据的Cronbachα值为0.718,表明合理的内部一致性和可靠性。

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