一种基于临床CT影像的肝内血管体积测量方法

肝脏血管体积不仅可以为临床疾病诊断提供重要参考,还对肝脏供血能力和肝脏储备功能的评估具有重要参考价值。本研究提出一种血管体积测量方法,利用置信连接和ITK-SNAP分割出肝内门静脉并进行空洞填补后,通过体素数目换算得到血管体积。该方法可快速、准确的计算出肝内门静脉的体积。实验采用10套不同规格的肝脏CT图像进行肝内门静脉血管体积测量,并选取3套数据与基于手工测量得到的血管体积进行对比。实验结果表明,通过本研究方法测量得到的体积与手工测量结果基本一致,利用统计学方法得到的肝内门静脉的体积为(11.316±1.080)m L。国家自然科学基金项目(61001144,61271336,61327001

Research on Parametric Modeling Method of Hepatic Vessel

肝癌是我国病死率最高的恶性肿瘤之一，现今治疗肝癌的有效手段只有手术切除治疗。但是因为肝脏血管结构的复杂性以及个体肝脏之间的差异性，肝脏手术通常具有非常高的风险性。从二维医学图像中将肝脏血管快速、精准地分割出来，清晰地显示肝脏血管的三维结构，帮助医生直观地看到肝脏血管的空间位置、三维形态、分支的管径大小以及分级情况，对制定精密的肝脏手术计划、进行精确的术前评估，从而提高手术的安全性，具有非常重要的意义。 本文针对肝脏CT图像，通过肝脏血管分割、肝脏血管骨架线的提取，最后实现肝脏血管的三维建模。本文主要从以下几个方面开展研究性工作： 首先，针对模糊连接分割算法在肝脏血管分割中需要手动设置阈值和...Liver cancer is one of malignant tumors with the highest mortality rate in our country, and at present there’s no effective treatment of liver cancer but surgical operation. As a result of the complexity of hepatic vascular structure and individual differences of the human liver, the liver surgical operation is usually of the high risk. Segmenting the hepatic vessel from the 2D medical image rapid...学位：工学硕士院系专业：信息科学与技术学院_计算机科学与技术学号：2302012115292

Vascular Segmentation in Hepatic CT Images Using Adaptive Threshold Fuzzy Connectedness Method

近年来模糊连接算法已经在医学图像分割中得到了应用.然而将此算法直接应用于肝脏血管分割时,由于其过高的计算成本以及需要手动选取阈值,分割效率并不是非常理想.为此,提出一种基于查找表计算模糊场景的方法,能够使模糊连接算法的运算速度提高1.5~2倍;同时提出一种类分水岭的自适应阈值搜索算法,能够对肝脏血管分割的阈值进行自动选取,从而实现了整个模糊连接分割流程的自动化处理.并且以3套肝脏CT数据为实验对象进行了验证,实验结果表明基于查找表的计算方法具有高效性,并且根据自适应阈值进行肝脏血管分割能产生正确的结果.In recent years,fuzzy connectedness method(FCM)was used to extract fuzzy objects from medical images and show its effectiveness.However,when FCM was applied to hepatic vessel segmentation task,two problems may occur.One is the expensive computational cost;the other is the difficulty of choosing aproper threshold value.In this paper,an accelerated method which is based on a lookup table is presented first.This method can reduce the connectivity scene calculation time and achieve a speed-up factor of about 1.5-2.When this step finished,FCM needs a threshold to generate the final result.Currently this threshold can only be guessed by users.Since different thresholds may generate different results,aproper threshold is usually needed.By analyzing the hepatic vessel structure,a watershed-like method can then be used to find the threshold.Experiments based on three different data sets demonstrate the efficiency of the lookup table method.These experiments also show that the threshold found by this method can usually generate correct segmentation results.国家自然科学基金(61001144;61102137;61327001