基于局部直方图和概率图谱相关图的非对比 CT 三维半自动肝脏分割方法。
Three-dimensional semiautomatic liver segmentation method for non-contrast computed tomography based on a correlation map of locoregional histogram and probabilistic atlas.
机构信息
Department of Biomaterials Science, Osaka University Graduate School of Dentistry, 1-8 Yamadaoka, Suita, Osaka 565-0871, Japan.
College of Information Science and Engineering, Ritsumeikan University, 1-1-1 Nojihigashi, Kusatsu, Shiga 525-8577, Japan.
出版信息
Comput Biol Med. 2014 Dec;55:79-85. doi: 10.1016/j.compbiomed.2014.10.003. Epub 2014 Oct 14.
BACKGROUND
We sought to evaluate a new regional segmentation method for use with three-dimensional (3D) non-contrast abdominal CT images and to report the preliminary results.
METHODS
The proposed method was evaluated in ten cases. Manually segmented areas were used as the gold standard for evaluation. To compare the standard and the extracted liver regions, the degree of coincidence R% was redefined by transforming a volumetric overlap error. We also evaluated the influence of varying the density window size in terms of setting the starting points.
RESULTS
We confirmed in ten cases that our method could segment the liver region more precisely than the conventional method. A size of window 15 voxels was optimal as the starting point in all cases.
CONCLUSIONS
We demonstrated the accuracy of a 3D semiautomatic liver segmentation method for non-contrast CT. This method promises to offer radiologists a time-efficient segmentation aid.
背景
我们旨在评估一种新的三维（3D）非对比腹部 CT 图像区域分割方法，并报告初步结果。
方法
该方法在十例病例中进行了评估。手动分割区域被用作评估的金标准。为了比较标准和提取的肝脏区域，通过转换体积累加误差来重新定义符合度 R%。我们还评估了改变密度窗大小对设置起点的影响。
结果
我们在十例病例中证实，我们的方法可以比传统方法更精确地分割肝脏区域。在所有情况下，窗口大小为 15 个体素是最佳的起点。
结论
我们证明了一种用于非对比 CT 的 3D 半自动肝脏分割方法的准确性。这种方法有望为放射科医生提供一种高效的分割辅助工具。
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