本文選題：肺部血管分割 + 三維區(qū)域生長算法　； 參考：《山東師范大學(xué)》2017年碩士論文

【摘要】：計算機斷層掃描CT影像具有空間分辨率高等特點,已成為肺部疾病影像學(xué)診斷的首選方式,而醫(yī)生多數(shù)采用肺部強化CT圖像來對肺部疾病診斷和治療。CT圖像中肺部血管的分割,是肺炎、肺動脈栓塞等肺部疾病計算機輔助檢測和診斷的基礎(chǔ)與關(guān)鍵,具有重要的研究意義與應(yīng)用價值。在文獻閱讀的基礎(chǔ)上,結(jié)合肺部血管的特點,提出一種基于三維區(qū)域生長法的肺部血管分割算法,主要有三方面的研究工作。(1)相關(guān)理論基礎(chǔ)的學(xué)習(xí)與研究。學(xué)習(xí)了肺部相關(guān)醫(yī)學(xué)和醫(yī)學(xué)圖像知識,以及肺部血管和氣管的走行。研究了現(xiàn)階段肺部血管的分割方法,并且重點分析了基于區(qū)域生長算法肺部血管分割近幾年的研究成果。通過閱讀文獻,明晰了現(xiàn)階段國內(nèi)外關(guān)于肺部血管分割的研究現(xiàn)狀。(2)算法設(shè)計與分析。整個算法主要包括圖像預(yù)處理、肺泡分割、肺氣管分割、肺血管分割等4個方面。針對肺泡分割,提出漫水填充分割算法,解決了左右肺連接和過分分割問題;針對肺部氣管分割,提出了一種26-鄰域三維區(qū)域生長算法,精確分割出肺部氣管;針對肺血管分割,首先將肺氣管像素從CT圖像中剔除,隨后應(yīng)用26-鄰域三維區(qū)域生長法分割。(3)算法實現(xiàn)與驗證。利用軟件平臺Visual Studio 2010,結(jié)合Open CV和VTK等第三方開源庫,運用C++語言編程實現(xiàn)算法,通過實驗結(jié)果來驗證算法的可行性與有效性,運用圖像分割評價指標給出定量評價。研究的創(chuàng)新之處是,(1)使用雙閾值作為三維區(qū)域生長的生長規(guī)則,在種子點手動選取之后,根據(jù)方差和灰度均值作為生長規(guī)則,從而提高分割的精度。(2)針對肺泡分割存在易過度分割、左右肺部不能分離等問題,提出一種全自動的基于漫水填充算法的肺泡分割方法。研究存在的不足是,肺毛細血管分割不完全,分割的自動化程度需進一步提高。
[Abstract]:Computed tomography (CT) has the characteristics of high spatial resolution and has become the first choice for imaging diagnosis of lung diseases. Most doctors use enhanced CT images of lung to diagnose lung diseases and treat pulmonary vessels in.CT images, which are the basis of computer aided detection and diagnosis of pneumonia, pulmonary embolism and other pulmonary diseases. Base and key, it has important research significance and application value. On the basis of literature reading, combined with the characteristics of pulmonary blood vessels, a new algorithm of pulmonary vascular segmentation based on three dimensional region growth method is proposed, which mainly has three aspects of research. (1) study and Research on the basis of related theories. Knowledge, and the movement of pulmonary vessels and trachea. The segmentation methods of pulmonary vessels at the present stage are studied, and the results of recent years' research on the segmentation of pulmonary vessels based on regional growth algorithm are emphatically analyzed. Through reading literature, the current research status on pulmonary vascular segmentation at home and abroad is clarified. (2) algorithm design and analysis. The whole algorithm is designed and analyzed. Mainly including image preprocessing, alveolar segmentation, lung trachea segmentation, pulmonary vascular segmentation, and other 4 aspects. Aiming at alveolar segmentation, a diffuse filling segmentation algorithm is proposed to solve the problem of left and right lung connections and excessive segmentation. A new 26- neighborhood three-dimensional region growth algorithm is proposed for the segmentation of lung and trachea, and the lung trachea is segmented accurately. Segmentation, first remove the lung trachea pixels from the CT image, then use the 26- neighborhood three-dimensional region growth method. (3) the algorithm implementation and verification. Using the software platform Visual Studio 2010, combined with Open CV and VTK, the three party open source library, using C++ language programming to implement the algorithm, through the experimental results to verify the feasibility and effectiveness of the algorithm. Quantitative evaluation is given with the evaluation index of image segmentation. The innovation of the study is: (1) using double threshold as the growth rule of three-dimensional region growth, after the manual selection of the seed points, according to the variance and the mean value as the growth rule, and thus improve the precision of the segmentation. (2) there is an easy over segmentation for the pulmonary alveolus segmentation, and the left and right lungs can not be divided. In order to solve the problem, a fully automatic method of pulmonary alveolus segmentation based on diffuse filling algorithm is proposed. The shortcomings of the study are that the segmentation of lung capillaries is incomplete and the degree of automation of the segmentation needs to be further improved.
【學(xué)位授予單位】：山東師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：R816.4;TP391.41

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