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EFFICIENT GRAPH CUTS BASED EXTRACTION OF VERTEBRAL COLUMN AND RIBS IN LUNG MDCT IMAGES

机译:基于肺部脊柱图像的高效图削减脊柱和肋骨图像

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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:提供了一种基于图表切割的全自动新算法,用于准确和快速分割和分离多探测器计算机断层扫描(MDCT)图像中的人椎体柱和肋骨。分割后面是一项两步隔离方法,以去除胸骨,锁骨和肩胛骨等未分段零件。在18名患者数据集上测试了所提出的算法,与每个数据集中的5个切片相比放射科医师提供的参考描绘相比。在2-D(带4和8个邻居)和3-D(具有6和26个邻居)图中进行实验,具有宽范围的参数值。基于我们的评估,2-D,4个邻居图显示了具有低运行时间的高性能(骰子相似度系数≈92.5%)(对于346片数据集57.86秒),建议用于椎体柱的准确和快速分割肋骨。

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