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首页> 外文会议>2012 6th International Conference on New Trends in Information Science, Service Science and Data Mining >A high-speed method for liver segmentation on abdominal CT image
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A high-speed method for liver segmentation on abdominal CT image

机译：腹部CT图像的高速肝分割方法

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This paper presents a high-speed liver segmentation method applied on abdominal CT image. Firstly, based on the morphological feature of the liver region under various window-level settings, we apply the region-growing algorithm to remove other tissues such as skeleton, skin, kidney and stomach, and hence the discrete points of the liver region can be acquired. Secondly, we recover the liver region from the original image by calculating the coordinates of the discrete points. Finally, in order to get more accurate segmentation results, the gradient information based edge correction and three-dimensional restoration are adopted to optimize the recovered liver image. Compared with other liver segmentation methods, our method has lower time complexity, which can satisfy the demands of real-time processing.
机译：本文提出了一种用于腹部CT图像的高速肝分割方法。首先，根据不同窗口级别设置下肝脏区域的形态特征，我们应用区域增长算法去除骨骼，皮肤，肾脏和胃等其他组织，因此可以将肝脏区域的离散点获得。其次，我们通过计算离散点的坐标从原始图像恢复肝脏区域。最后，为了获得更准确的分割结果，采用基于梯度信息的边缘校正和三维还原对肝脏图像进行了优化。与其他肝脏分割方法相比，该方法具有较低的时间复杂度，可以满足实时处理的需求。

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