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Automatic Left and Right Heart Segmentation Using Power Watershed and Active Contour Model without Edge

机译:使用功率分水岭和无边缘主动轮廓模型自动进行左右心分割

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PurposeIn this paper, we present an automatic method to segment a whole heart and separate left and right heart regions in cardiac computed tomography angiography (CTA) efficiently. Methods First, we smooth the images by applying filters to remove noise. Second, the volume of interest (VOI) is detected by using k-means clustering. In this step, the whole heart is coarsely extracted, and it is used for seed volumes in the next step. Third, we detect seed volumes using a geometric analysis based on anatomical information and separate the left and right heart with power watershed. Finally, we refine the left and right sides of the heart using active contour model without edge, which used region-based information for a more accurate segmentation. ResultsIn experimental results using twenty clinical datasets, the average segmentation error was less than 5%. The average processing time was 51.66±3.35 s. ConclusionsThe proposed method extracts the left and right heart accurately, demonstrating that this approach can assist the cardiologist.
机译:目的在本文中,我们提出了一种自动方法,可以在心脏计算机断层扫描血管造影(CTA)中有效地分割整个心脏并分离左,右心脏区域。方法首先,我们通过应用滤镜消除噪声来平滑图像。其次,通过使用k均值聚类检测感兴趣的体积(VOI)。在此步骤中,将整个心脏粗略地提取出来,并在下一步中用于种子量。第三,我们使用基于解剖学信息的几何分析来检测种子量,并用功率分水岭将左右心脏分开。最后,我们使用无边缘的活动轮廓模型精炼心脏的左侧和右侧,该模型使用基于区域的信息进行更精确的分割。结果在使用20个临床数据集的实验结果中,平均分割误差小于5%。平均处理时间为51.66±3.35 s。结论所提出的方法可以准确地提取左右心脏,表明这种方法可以帮助心脏病专家。

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