首页> 外文期刊>Journal of Medical Imaging and Health Informatics >Direct 3D Organ Extraction Method in Virtual Human-Body Color Volume Image
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Direct 3D Organ Extraction Method in Virtual Human-Body Color Volume Image

机译:虚拟人体颜色体积图像中的直接3D器官提取方法

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摘要

Extracting 3D structures from voxel based images can make doctors more directly observe the situation of the target in the clinic, making it easier for doctors to diagnose the condition and make the medicine teaching more directly and easier to understand. For this purpose, we propose a 3D volume image segmentation method based on the max-flow/min-cut algorithm. Our segmentation method can be applied directly to 3D volume image. After users marking small amount tags (foreground and background pixels), we put forward a method to use a directed connected graph structure to represent the volume image. In the directed connected graph, in order to speed up the efficiency of the segmentation in subsequent steps, we divide each voxel node in the graph into different color ranges, and each color range match up with an auxiliary node. In order to divide the color range more finely, we propose a method to calculate the color similarity. We then use the max-flow/min-cut algorithm to segment the directed connected graph. The result of experiments performed in multiple sets of slice images shows that our proposed method improves the efficiency, reduces human error on the 3D volume image segmentation task, and the result is complete and accurate.
机译:从Voxel基础的图像中提取3D结构可以使医生更直接观察诊所的目标情况,使医生更容易诊断病情并使医学教学更直接,更容易理解。为此目的,我们提出了一种基于MAX-FLUS / MIN切割算法的3D体积图像分割方法。我们的分段方法可以直接应用于3D体积图像。在用户标记少量标签(前景和背景像素)后,我们提出了一种方法来使用定向连接的图形结构来表示卷图像。在定向连接图中,为了在后续步骤中加速分段的效率,我们将图形中的每个体素节点划分为不同的颜色范围,并且每个颜色范围与辅助节点匹配。为了更精细地划分颜色范围,我们提出了一种计算颜色相似性的方法。然后,我们使用MAX-FLUS / MIN-CUT算法对定向连接的图进行分割。在多组切片图像中执行的实验结果表明,我们的提出方法提高了效率,降低了3D卷图像分割任务的人为错误,结果是完整和准确的。

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