【摘要】：隨著現(xiàn)代醫(yī)學(xué)成像技術(shù)的不斷進(jìn)步,根據(jù)CT圖像進(jìn)行分析和診斷病情,已經(jīng)成為當(dāng)今最主要的方法之一。肝臟血管疾病是影響人們健康的重要疾病之一。所以,在肝臟CT圖像中分析血管具有非常關(guān)鍵的意義。但是,肝臟血管的系統(tǒng)非常復(fù)雜,要想得到比較完整的血管信息,需要采用合理的圖像分割技術(shù)對(duì)肝臟血管實(shí)施分割,才能對(duì)肝臟血管具有更加完整的認(rèn)識(shí)與理解。在各種肝臟血管分割的方法里,區(qū)域生長(zhǎng)算法是應(yīng)用比較廣泛的。所以本文在傳統(tǒng)區(qū)域生長(zhǎng)算法的基礎(chǔ)上,以原始腹部CT圖像作為輸入,采用改進(jìn)的區(qū)域生長(zhǎng)算法對(duì)肝臟血管進(jìn)行了分割。進(jìn)行的研究工作主要有:(1)理論基礎(chǔ)的研究。對(duì)醫(yī)學(xué)圖像的相關(guān)知識(shí),特別是CT圖像的特點(diǎn)進(jìn)行了學(xué)習(xí)和研究。對(duì)區(qū)域生長(zhǎng)算法的相關(guān)知識(shí)和應(yīng)用進(jìn)行了學(xué)習(xí)。并且研究了基于區(qū)域生長(zhǎng)算法的肝臟血管分割的研究背景和近幾年的研究成果,通過閱讀文獻(xiàn),了解了現(xiàn)階段國內(nèi)外關(guān)于采用區(qū)域生長(zhǎng)算法分割肝臟血管的研究現(xiàn)狀,并結(jié)合肝臟血管的特點(diǎn),構(gòu)建了本文的算法框架。(2)圖像預(yù)處理方法的選擇。簡(jiǎn)單介紹了CT圖像的特點(diǎn)與CT圖像中常用的肝臟血管分割方法,根據(jù)肝臟內(nèi)血管的特點(diǎn),選擇合適的圖像預(yù)處理方法,以及肝臟血管的分割方法。(3)區(qū)域生長(zhǎng)算法的改進(jìn)思路。首先簡(jiǎn)單的介紹了傳統(tǒng)區(qū)域生長(zhǎng)算法的基本理論和方法。通過分析傳統(tǒng)區(qū)域生長(zhǎng)算法的優(yōu)缺點(diǎn),提出粗分割和細(xì)分割相結(jié)合的改進(jìn)區(qū)域生長(zhǎng)算法,然后以改進(jìn)區(qū)域生長(zhǎng)算法的基本原理為基礎(chǔ),設(shè)計(jì)并實(shí)現(xiàn)了肝臟血管的三維分割,其中詳細(xì)描述了分割的具體流程、分割的方法以及所用到的相關(guān)技術(shù)。最后,對(duì)分割后的血管進(jìn)行了研究和分析,并且選擇相應(yīng)的優(yōu)化和可視化方法,對(duì)血管進(jìn)行了進(jìn)一步的處理。(4)實(shí)驗(yàn)驗(yàn)證。利用VS2010和Matlab軟件平臺(tái),以分割后的肝臟CT圖像序列為輸入,編寫算法的仿真實(shí)驗(yàn)程序,采用改進(jìn)的區(qū)域生長(zhǎng)算法進(jìn)行了分割實(shí)驗(yàn)。并且借助于可視化工具包VTK,對(duì)血管進(jìn)行了三維重建,呈現(xiàn)出血管的三維結(jié)構(gòu),使人們更加便于觀察血管。本文的算法主要是針對(duì)過去分割血管的一次性問題,采用粗分割和細(xì)分割相結(jié)合的分割方法,并且在最后的實(shí)驗(yàn)結(jié)果和分析中,不僅對(duì)本文算法的實(shí)驗(yàn)結(jié)果進(jìn)行了分析,而且把改進(jìn)算法和常規(guī)算法的實(shí)驗(yàn)分割結(jié)果進(jìn)行了比較與分析,證明了改進(jìn)的區(qū)域生長(zhǎng)方法在肝臟血管的分割中獲得的血管信息更全面,分割結(jié)果更準(zhǔn)確,同時(shí),對(duì)本文算法也進(jìn)行了性能的分析和比較,驗(yàn)證了本文算法的分割精度和可行性。
[Abstract]:With the development of modern medical imaging technology, it has become one of the most important methods to analyze and diagnose the disease according to CT images. Hepatic vascular disease is one of the most important diseases affecting people's health. Therefore, it is very important to analyze blood vessels in CT images of liver. However, the system of hepatic vessels is very complex. In order to obtain more complete vascular information, it is necessary to use reasonable image segmentation technology to segment hepatic blood vessels in order to have a more complete understanding and understanding of liver blood vessels. Among the methods of hepatic vascular segmentation, the region growth algorithm is widely used. Therefore, based on the traditional region growth algorithm, the original abdominal CT image is used as input, and the improved region growth algorithm is used to segment the liver vessels. The main research work is as follows: (1) theoretical basis research. The related knowledge of medical images, especially the characteristics of CT images, is studied and studied. The knowledge and application of region growth algorithm are studied. And the research background of liver vascular segmentation based on regional growth algorithm and the research results in recent years are studied. Through reading the literature, the current research status of using regional growth algorithm to segment liver blood vessels at home and abroad is understood. Combined with the characteristics of hepatic vessels, the algorithm framework is constructed. (2) the selection of image preprocessing methods. This paper briefly introduces the characteristics of CT image and the commonly used methods of hepatic vascular segmentation in CT image. According to the characteristics of intrahepatic vessels, the appropriate image preprocessing method is selected. And the segmentation method of hepatic vessels. (3) the improvement of region growth algorithm. Firstly, the basic theory and method of traditional region growth algorithm are introduced briefly. By analyzing the advantages and disadvantages of the traditional region growth algorithm, an improved region growth algorithm combining coarse segmentation and fine segmentation is proposed. Based on the basic principle of the improved region growth algorithm, the 3D segmentation of hepatic vessels is designed and realized. Detailed description of the specific process of segmentation, segmentation methods and the use of relevant technologies. Finally, the segmented blood vessels are studied and analyzed, and the corresponding optimization and visualization methods are selected to further deal with the blood vessels. (4) Experimental verification. Based on the VS2010 and Matlab software platform and taking the segmented liver CT image sequence as input, the simulation program of the algorithm is compiled, and the improved region growth algorithm is used to carry out the segmentation experiment. The 3D reconstruction of blood vessels is carried out with the aid of VTK, which presents the three-dimensional structure of blood vessels and makes it easier for people to observe blood vessels. The algorithm of this paper mainly aims at the one-time problem of segmenting blood vessels in the past, and adopts the method of combining coarse segmentation and fine segmentation. In the final experiment and analysis, not only the experimental results of this algorithm are analyzed. Moreover, the experimental results of the improved algorithm and the conventional algorithm are compared and analyzed. It is proved that the improved region growth method has more comprehensive information and more accurate segmentation results in the segmentation of liver blood vessels. The performance of this algorithm is also analyzed and compared to verify the segmentation accuracy and feasibility of this algorithm.
【學(xué)位授予單位】：山東師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：R816.5;TP391.41

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