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Efficient graph cuts based extraction of vertebral column and ribs in lung MDCT images

机译:基于有效图割的肺部MDCT图像中脊柱和肋骨的提取

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A fully automatic novel algorithm based on graph cuts is presented for accurate and fast segmentation and isolation of human vertebral column and ribs in multi detector computed tomography (MDCT) images. The segmentation is followed by a two-step isolation method to remove mis-segmented parts such as the sternum, clavicle and scapula. The proposed algorithm was tested on 18 patient datasets, with 5 slices from each dataset compared to the reference delineation provided by a radiologist. The experiments were performed on both 2-D (with 4 and 8 neighbours) and 3-D (with 6 and 26 neighbours) graphs with wide range of parameter values. Based on our evaluation, the 2-D, 4 neighbours graph shows high performance (Dice similarity coefficient ≈ 92.5%) with low running time (57.86 s for a 346 slice dataset) and is recommended for accurate and fast segmentation of the vertebral column and ribs.
机译:提出了一种基于图形切割的新颖新颖算法,用于在多探测器计算机断层扫描(MDCT)图像中准确,快速地分割和隔离人的脊柱和肋骨。分割之后是两步隔离方法,以去除错误分割的部分,例如胸骨,锁骨和肩骨。该算法在18个患者数据集中进行了测试,每个数据集中有5个切片与放射科医生提供的参考轮廓进行了比较。在具有广泛参数值范围的2-D(具有4和8个邻居)和3-D(具有6和26个邻居)图上进行了实验。根据我们的评估,二维,4邻域图显示了高性能(Dice相似系数≈92.5%),运行时间短(对于346切片数据集为57.86 s),建议对椎骨柱和椎体进行准确,快速的分割肋骨。

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