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A high-speed method for liver segmentation on abdominal CT image

机译:腹部CT图像肝脏分割的高速方法

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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:本文介绍了施用在腹部CT图像上的高速肝脏分段方法。首先,基于各种窗口水平设置下肝脏区域的形态学特征,我们应用地区越来越多的算法去除其他组织,如骨架,皮肤,肾脏和胃,因此肝脏区域的离散点可以是获得。其次,我们通过计算离散点的坐标来从原始图像中恢复肝脏区域。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恢复来优化恢复的肝脏图像。与其他肝脏分段方法相比,我们的方法具有较低的时间复杂性,可以满足实时处理的需求。

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