【摘要】：磁共振成像作為主要的醫(yī)學(xué)影像技術(shù)之一,為輔助臨床診斷治療提供重要的圖像信息和量化信息。由于脂肪在磁共振成像中長(zhǎng)T2,短T1的特性,導(dǎo)致脂肪在磁共振圖像中是高亮信號(hào),進(jìn)而會(huì)影響圖像對(duì)比度,并可能會(huì)掩蓋一些潛在的病變,從而影響臨床診斷。因此,在磁共振圖像中抑制脂肪信號(hào)有很大的意義。Dixon技術(shù)不僅能夠抑制脂肪信號(hào),同時(shí)還能得到脂肪圖。兩點(diǎn)Dixon技術(shù)因掃描效率較高、并能靈活選擇回波時(shí)間,所以在臨床上有較廣泛的應(yīng)用。然而在圖像噪聲較大、存在偽影和運(yùn)動(dòng)等情況下,基于區(qū)域增長(zhǎng)算法的兩點(diǎn)Dixon技術(shù)會(huì)因?yàn)檎`差傳播和累積導(dǎo)致最終的水和脂肪分離發(fā)生錯(cuò)誤。本文提出了一種基于間隔采樣和區(qū)域增長(zhǎng)的兩點(diǎn)Dixon水脂分離新方法,能有效減少誤差傳播和累積,得到更準(zhǔn)確的水脂分離結(jié)果。提出方法的主要步驟為:首先對(duì)求得的場(chǎng)向量圖進(jìn)行間隔采樣獲得四對(duì)子向量圖,目的是降低突變相位對(duì)結(jié)果的影響;然后對(duì)四對(duì)子向量圖分別運(yùn)用區(qū)域增長(zhǎng)算法,得到四幅子向量圖;隨后再對(duì)四幅子向量圖進(jìn)行平滑校正操作,使子向量圖的空間相位更加準(zhǔn)確;最后,把四幅子向量圖合并校正得到最終的需要求解的向量圖。本文方法的創(chuàng)新之處在于:1.利用間隔采樣操作同時(shí)得到四幅子圖像,在后續(xù)處理中可相互約束并且可利用的圖像信息更加豐富;2.通過(guò)間隔采樣,把突變相位分配到四幅子圖,使得四幅子圖的相同區(qū)域同時(shí)出現(xiàn)突變相位的幾率變低;3.區(qū)域增長(zhǎng)算法和間隔采樣相結(jié)合,使得因突變相位導(dǎo)致的誤差傳播和累積可限制在單幅子圖中,降低了誤差傳播對(duì)全局相位估計(jì)的影響;4.利用子圖像的獨(dú)立性可進(jìn)行并行運(yùn)算,減少算法運(yùn)行時(shí)間。本文分別用了仿真實(shí)驗(yàn)和多組臨床數(shù)據(jù)對(duì)算法進(jìn)行驗(yàn)證。仿真相位的實(shí)驗(yàn)結(jié)果表明,在存在多處相位突變的情況下,本文提出方法發(fā)生錯(cuò)誤的像素點(diǎn)明顯比原區(qū)域增長(zhǎng)算法要少。噪聲仿真實(shí)驗(yàn)結(jié)果表明本文方法能降低噪聲對(duì)水脂分離結(jié)果的影響。真實(shí)數(shù)據(jù)水脂分離結(jié)果表明本文提出方法更穩(wěn)定和準(zhǔn)確。算法運(yùn)行時(shí)間是原基于區(qū)域增長(zhǎng)的兩點(diǎn)Dixon方法的三分之一左右,該優(yōu)勢(shì)在圖像數(shù)據(jù)矩陣較大時(shí)將更明顯。
[Abstract]:As one of the main medical imaging techniques, magnetic resonance imaging (MRI) provides important image information and quantitative information for clinical diagnosis and treatment. Because of the long T _ 2 and short T _ 1 characteristics of fat in magnetic resonance imaging, fat is a highlight signal in magnetic resonance imaging, which will affect the contrast of the image, and may cover up some potential lesions, thus affecting the clinical diagnosis. Therefore, it is of great significance to suppress fat signal in magnetic resonance imaging. Dixon technique can not only suppress fat signal, but also obtain fat map. Two-point Dixon is widely used in clinic because of its high scanning efficiency and flexible choice of echo time. However, in the case of large image noise, artifact and motion, the error in the final separation of water and fat will occur due to the error propagation and accumulation of the two-point Dixon technique based on the region growth algorithm. In this paper, a new two-point Dixon water-lipid separation method based on interval sampling and regional growth is proposed, which can effectively reduce the error propagation and accumulation, and obtain more accurate results of water-lipid separation. The main steps of the proposed method are as follows: firstly, four pairs of subvector graphs are obtained by interval sampling of the obtained field vector graphs, the purpose of which is to reduce the effect of the abrupt phase on the results, and then the region growth algorithm is applied to the four pairs of subvector graphs. Four subvector graphs are obtained, and then the four subvector graphs are smoothed and corrected to make the spatial phase of the subvector graphs more accurate. Finally, the four subvector graphs are combined and corrected to obtain the final vector graphs that need to be solved. The innovation of the method of this paper lies in: 1. Four sub-images can be obtained simultaneously by interval sampling operation, which can constrain each other and enrich the available image information in subsequent processing. Through interval sampling, the abrupt phase is allocated to four subgraphs, which makes the probability of abrupt phase appearing in the same region of the four subgraphs to be lower. The combination of region growth algorithm and interval sampling makes the error propagation and accumulation caused by the abrupt phase can be restricted to a single subgraph, which reduces the influence of error propagation on the global phase estimation. Using the independence of the subimage, the parallel operation can be carried out, and the running time of the algorithm can be reduced. In this paper, simulation experiments and multiple sets of clinical data are used to verify the algorithm. The experimental results show that in the presence of multiple phase mutations, the number of pixels with errors in the proposed method is obviously less than that of the original region growth algorithm. The results of noise simulation show that the proposed method can reduce the effect of noise on the separation of water and lipid. The real data show that the proposed method is more stable and accurate. The running time of the algorithm is about 1/3 of the original two-point Dixon method based on region growth, which will be more obvious when the image data matrix is large.
【學(xué)位授予單位】：南方醫(yī)科大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.41;R445.2

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相關(guān)期刊論文 前2條

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本文編號(hào)：2191276