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首页> 外文会议>Image Processing pt.3; Progress in Biomedical Optics and Imaging; vol.8,no.31; Proceedings of SPIE-The International Society for Optical Engineering; vol.6512 pt.3 >Automated segmentation of hepatic vessel trees in non-contrast X-ray CT images
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Automated segmentation of hepatic vessel trees in non-contrast X-ray CT images

机译：非对比X射线CT图像中肝血管树的自动分割

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摘要

Hepatic vessel trees are the key structures in the liver. Knowledge of the hepatic vessel trees is important for liver surgery planning and hepatic disease diagnosis such as portal hypertension. However, hepatic vessels cannot be easily distinguished from other liver tissues in non-contrast CT images. Automated segmentation of hepatic vessels in non-contrast CT images is a challenging issue. In this paper, an approach for automated segmentation of hepatic vessels trees in non-contrast X-ray CT images is proposed. Enhancement of hepatic vessels is performed using two techniques: (1) histogram transformation based on a Gaussian window function; (2) multi-scale line filtering based on eigenvalues of Hessian matrix. After the enhancement of hepatic vessels, candidate of hepatic vessels are extracted by thresholding. Small connected regions of size less than 100 voxels are considered as false-positives and are removed from the process. This approach is applied to 20 cases of non-contrast CT images. Hepatic vessel trees segmented from the contrast-enhanced CT images of the same patient are used as the ground truth in evaluating the performance of the proposed segmentation method. Results show that the proposed method can enhance and segment the hepatic vessel regions in non-contrast CT images correctly.
机译：肝血管树是肝脏中的关键结构。肝血管树的知识对于肝手术计划和肝病诊断（例如门静脉高压症）很重要。但是，在非对比CT图像中，肝血管很难与其他肝脏组织区分开。在非对比CT图像中自动分割肝血管是一个具有挑战性的问题。本文提出了一种在非对比X射线CT图像中自动分割肝血管树的方法。肝血管的增强使用两种技术进行：（1）基于高斯窗函数的直方图变换； （2）基于Hessian矩阵特征值的多尺度线滤波。增强肝血管后，通过阈值提取候选肝血管。大小小于100体素的小连接区域被认为是假阳性，并从过程中删除。该方法适用于20例非对比CT图像。从同一患者的对比增强CT图像中分割出的肝血管树被用作评估所提出分割方法性能的依据。结果表明，所提出的方法可以正确地增强和分割非造影CT图像中的肝血管区域。

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