發(fā)布時(shí)間：2018-10-08 10:26

【摘要】：據(jù)統(tǒng)計(jì)，，心臟疾病已經(jīng)逐漸成為了當(dāng)今社會(huì)人類的頭號(hào)殺手，正嚴(yán)重威脅和危害著人民群眾的健康。左心室通過周期性的收縮、舒張、扭轉(zhuǎn)等運(yùn)動(dòng)形式將左心室內(nèi)的血液泵入全身各組織器官，在心臟活動(dòng)中的作用尤其重要。因此，可將其運(yùn)動(dòng)形式異常、形態(tài)異常等作為判斷心臟是否產(chǎn)生病變的重要參考依據(jù)。研究表明，在很多疾病條件下，心臟運(yùn)動(dòng)的程度及形式會(huì)產(chǎn)生較大變化。因而，對(duì)左心室進(jìn)行運(yùn)動(dòng)跟蹤對(duì)于心功能正常與否的判定具有積極的意義。 實(shí)時(shí)三維超聲技術(shù)和心臟MR技術(shù)均是無創(chuàng)的心臟運(yùn)動(dòng)觀察方法，本文將圖像處理相關(guān)技術(shù)，如圖像濾波、圖像配準(zhǔn)、時(shí)間序列圖像分割以及心室輪廓邊緣跟蹤等運(yùn)用于左心室的運(yùn)動(dòng)跟蹤，針對(duì)實(shí)時(shí)三維超聲技術(shù)得到的左心室時(shí)間序列圖像，初步對(duì)心臟左心室運(yùn)動(dòng)情況進(jìn)行跟蹤分析，并進(jìn)行了左心室一個(gè)心動(dòng)周期內(nèi)的三維可視化重建。 本文的主要工作以及取得的成果如下： ①進(jìn)行了左心室超聲圖像預(yù)處理工作。綜合幾種常見的非線性濾波方法中值濾波、Lee濾波、形態(tài)學(xué)濾波對(duì)左心室超聲圖像進(jìn)行濾波處理，通過結(jié)果對(duì)比分析選取了形態(tài)學(xué)濾波方法作為圖像預(yù)處理方法。 ②進(jìn)行了左心室MR圖像配準(zhǔn)的研究。針對(duì)心臟磁共振圖像提出了一種新穎的Radon變換與功率譜結(jié)合的圖像配準(zhǔn)算法。該算法進(jìn)行的邊緣檢測過程不僅濾除了部分噪聲干擾，還使得輸入數(shù)據(jù)大大減少。利用Radon變換降維、快速提取有用信息的特點(diǎn)和功率譜的旋轉(zhuǎn)不變特性，很好地實(shí)現(xiàn)了左心室MR圖像配準(zhǔn)。 ③提出兩種左心室超聲圖像分割方法。第一種分割方法為利用時(shí)刻獨(dú)立脈沖耦合神經(jīng)網(wǎng)絡(luò)針對(duì)心臟扭轉(zhuǎn)運(yùn)動(dòng)中的左心室壁進(jìn)行精確定位以及邊緣輪廓提取；第二種分割方法利用與投影方法結(jié)合C-V水平集分割方法實(shí)現(xiàn)了左心室超聲序列圖像的自動(dòng)分割，為進(jìn)一步圖像配準(zhǔn)提供了優(yōu)秀的素材。算法首先綜合投影方法對(duì)左心室位置進(jìn)行粗定位，然后再對(duì)定位區(qū)域運(yùn)用C-V水平集方法進(jìn)行細(xì)分割。 ④實(shí)現(xiàn)了左心室運(yùn)動(dòng)跟蹤以及三維重建。對(duì)分割后左心室超聲時(shí)間序列圖像進(jìn)行了邊緣人工標(biāo)記跟蹤并對(duì)運(yùn)動(dòng)參數(shù)進(jìn)行測量統(tǒng)計(jì)分析；在OpenGL平臺(tái)下，利用最短對(duì)角線法對(duì)左心室腔輪廓進(jìn)行三維表面重建，實(shí)現(xiàn)了基于輪廓拼接的左心室三維重建。 本文提出的基于圖像處理的心臟運(yùn)動(dòng)跟蹤算法可行性高，其中涉及的圖像配準(zhǔn)、圖像分割等算法具有獨(dú)創(chuàng)性，有一定的臨床應(yīng)用價(jià)值，希望在以后的研究中能進(jìn)一步完善分割以及運(yùn)動(dòng)跟蹤算法并盡快應(yīng)用于臨床分析。
[Abstract]:According to statistics, heart disease has gradually become the leading killer of human beings, which is seriously threatening and endangering the health of the people. The left ventricle pumps blood into the whole body through periodic contraction, relaxation and torsion, which plays an important role in cardiac activity. Therefore, it can be used as an important reference to judge whether the heart has pathological changes. Studies have shown that the degree and form of cardiac movement vary greatly under many disease conditions. Therefore, the left ventricular movement tracking is of positive significance for the determination of normal cardiac function. Real-time three-dimensional ultrasound and cardiac MR are non-invasive methods to observe cardiac motion. In this paper, image processing techniques, such as image filtering, image registration, etc. Time series image segmentation and contour tracking are used to track the motion of the left ventricle. In view of the time series images of the left ventricle obtained by real-time three-dimensional ultrasound, the motion of the left ventricle is tracked and analyzed preliminarily. Three-dimensional visual reconstruction of left ventricle during a cardiac cycle was performed. The main work and achievements are as follows: 1 preprocessing of left ventricular ultrasound image. In this paper, several common nonlinear filtering methods, median filter and Lee filter, are synthesized. Morphological filtering is used to filter the left ventricular ultrasound image. The morphological filtering method is selected as the image preprocessing method through the comparative analysis of the results. 2 the registration of left ventricular MR images was studied. A novel image registration algorithm combining Radon transform and power spectrum is proposed for cardiac magnetic resonance imaging. The edge detection process of the algorithm not only filters out some noise interference, but also reduces the input data greatly. The feature of useful information and the rotation invariance of power spectrum are extracted quickly by using Radon transform to reduce the dimension. The registration of left ventricular MR image is well realized. 3 two methods of left ventricular ultrasound image segmentation were proposed. The first method is to accurately locate the left ventricular wall and extract the edge contour of the left ventricular wall in torsional motion by using the time-independent pulse coupled neural network. The second method uses the projection method and the C-V level set segmentation method to realize the automatic segmentation of the left ventricular ultrasound sequence image, which provides excellent materials for the further image registration. The algorithm firstly combines projection method to locate the position of left ventricle rough, then subdivides the location area by C-V level set method. 4 left ventricular motion tracking and three-dimensional reconstruction were realized. The edge of the segmented left ventricular ultrasound time series images was tracked with artificial markers and the motion parameters were measured and analyzed. The three-dimensional surface reconstruction of left ventricular cavity contour was carried out by using the shortest diagonal method under OpenGL platform. The three-dimensional reconstruction of left ventricle based on contour splicing is realized. The proposed heart motion tracking algorithm based on image processing is highly feasible. The image registration and image segmentation algorithms involved are original and have certain clinical application value. It is hoped that the segmentation and motion tracking algorithms will be further improved and applied to clinical analysis as soon as possible.
【學(xué)位授予單位】：重慶大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：R310;TP391.41

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本文編號(hào)：2256425