同步輻射X射線同軸相襯成像算法研究及生物醫(yī)學(xué)應(yīng)用
發(fā)布時間：2018-07-28 16:41
【摘要】：傳統(tǒng)的X射線吸收成像是利用樣品不同部分對X射線的吸收不同而成像的。但對于生物軟組織等以輕元素為主的樣品，由于其對X射線吸收差別很小，吸收襯度的成像方法很難獲得它的結(jié)構(gòu)信息。近年來同步輻射光源的迅速發(fā)展使得利用X射線的相位襯度成像成為研究的一個焦點。由于X射線能量在10KeV或更高時，生物組織對X射線的相移是吸收的一千倍以上，所以利用X射線的相位信息成像，將會大大提高成像質(zhì)量。常見的相襯成像方法中，同軸相襯成像易于實現(xiàn)，應(yīng)用廣泛，而相位恢復(fù)算法是同軸相襯成像中重要的一環(huán)。本文主要研究了同軸相襯成像原理和相位恢復(fù)算法，及同軸相襯成像在生物醫(yī)學(xué)中的應(yīng)用。 本文首先建立了X射線和物質(zhì)相互作用的關(guān)系模型，然后從光的自由空間傳播的菲涅爾-基爾霍夫衍射公式出發(fā)，導(dǎo)出了基于維納格分布的同軸相襯成像模型，介紹了幾種相位恢復(fù)算法：CTF算法，一階Born近似算法，TIE算法，Bronnikov算法和MBA算法。并通過模擬實驗比較和分析了距離，吸收率，噪聲三種因素的變化對不同算法相位恢復(fù)結(jié)果的影響，得出結(jié)論：TIE算法和CTF算法都不耐噪聲，，MBA算法可以抑制噪聲但是只能用于弱吸收樣品。模擬的結(jié)果對實驗中選取最適的算法有重要的指導(dǎo)意義。然后本文提出了一種基于迭代的改進相位恢復(fù)算法，這種改進算法可以改善MBA算法只適用于弱吸收樣品的情況，并且可以利用MBA算法較好的抑制噪聲的性質(zhì)，隨后通過模擬實驗證實了這種算法可以適用于更廣的、非弱吸收樣品的情形，而且計算復(fù)雜度不會顯著增加。由于實際的成像樣品是復(fù)雜多樣的，很多情況下吸收性未知，所以這種改進算法有重要的現(xiàn)實意義。 本文在上海光源做了標準物理樣品和小鼠腦樣品的同軸相襯成像實驗，然后利用本文提出的相位恢復(fù)算法做相位恢復(fù)重構(gòu)。實驗結(jié)果表明，同軸相襯成像可以更好的區(qū)分軟組織不同成分，而且不同組織的重構(gòu)值之間有較大的區(qū)分度，可以獲得比吸收成像更多的組織結(jié)構(gòu)信息，實驗結(jié)果顯示出同軸相襯成像在對生物軟組織成像上的巨大潛力。
[Abstract]:Traditional X-ray absorption imaging is based on the different absorption of X-ray in different parts of the sample. However, for samples with light elements, such as biological soft tissue, the absorption contrast imaging method is difficult to obtain the structure information because the difference of X-ray absorption is very small. In recent years, the rapid development of synchrotron radiation light sources makes the use of X-ray phase contrast imaging become a focus of research. Because the phase shift of biological tissue to X-ray is more than one thousand times that of absorption when the energy of X-ray is higher than 10KeV, the imaging quality will be greatly improved by using the phase information of X-ray. Among the common phase contrast imaging methods, the coaxial phase contrast imaging is easy to realize and widely used, and the phase recovery algorithm is an important part of the coaxial phase contrast imaging. In this paper, the principle and phase recovery algorithm of coaxial phase contrast imaging and the application of coaxial phase contrast imaging in biomedicine are studied. In this paper, a model of the interaction between X-ray and matter is established, and then a coaxial phase contrast imaging model based on the Wiener distribution is derived from the Fresnel Kirchhoff diffraction formula for the free space propagation of light. This paper introduces several phase recovery algorithms: the first order Born approximation algorithm, the Bronnikov algorithm and the MBA algorithm. The effects of distance, absorptivity and noise on the phase recovery results of different algorithms are compared and analyzed by simulation experiments. It is concluded that both the CTF algorithm and the CTF algorithm can suppress noise but can only be used in weak absorption samples. The results of the simulation are of great significance to the selection of the optimal algorithm in the experiment. Then, an improved phase recovery algorithm based on iteration is proposed. This improved algorithm can improve the MBA algorithm which is only suitable for weak absorption samples, and can make use of the MBA algorithm to suppress noise. The simulation results show that the proposed algorithm can be used in the case of a wide range of non-weak absorption samples, and the computational complexity is not significantly increased. Because the actual imaging samples are complex and diverse, and the absorbability is unknown in many cases, this improved algorithm has important practical significance. In this paper, the coaxial phase contrast imaging experiments of standard physical samples and mouse brain samples are carried out at Shanghai Light Source, and then the phase recovery reconstruction is done by using the phase recovery algorithm proposed in this paper. The experimental results show that the coaxial phase contrast imaging can better distinguish different components of soft tissue, and there is a greater degree of differentiation between the reconstruction values of different tissues, so more information of tissue structure can be obtained than that of absorption imaging. The experimental results show the great potential of coaxial phase contrast imaging in the imaging of biological soft tissue.
【學(xué)位授予單位】：上海交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：R811;O434.1
[Abstract]:Traditional X-ray absorption imaging is based on the different absorption of X-ray in different parts of the sample. However, for samples with light elements, such as biological soft tissue, the absorption contrast imaging method is difficult to obtain the structure information because the difference of X-ray absorption is very small. In recent years, the rapid development of synchrotron radiation light sources makes the use of X-ray phase contrast imaging become a focus of research. Because the phase shift of biological tissue to X-ray is more than one thousand times that of absorption when the energy of X-ray is higher than 10KeV, the imaging quality will be greatly improved by using the phase information of X-ray. Among the common phase contrast imaging methods, the coaxial phase contrast imaging is easy to realize and widely used, and the phase recovery algorithm is an important part of the coaxial phase contrast imaging. In this paper, the principle and phase recovery algorithm of coaxial phase contrast imaging and the application of coaxial phase contrast imaging in biomedicine are studied. In this paper, a model of the interaction between X-ray and matter is established, and then a coaxial phase contrast imaging model based on the Wiener distribution is derived from the Fresnel Kirchhoff diffraction formula for the free space propagation of light. This paper introduces several phase recovery algorithms: the first order Born approximation algorithm, the Bronnikov algorithm and the MBA algorithm. The effects of distance, absorptivity and noise on the phase recovery results of different algorithms are compared and analyzed by simulation experiments. It is concluded that both the CTF algorithm and the CTF algorithm can suppress noise but can only be used in weak absorption samples. The results of the simulation are of great significance to the selection of the optimal algorithm in the experiment. Then, an improved phase recovery algorithm based on iteration is proposed. This improved algorithm can improve the MBA algorithm which is only suitable for weak absorption samples, and can make use of the MBA algorithm to suppress noise. The simulation results show that the proposed algorithm can be used in the case of a wide range of non-weak absorption samples, and the computational complexity is not significantly increased. Because the actual imaging samples are complex and diverse, and the absorbability is unknown in many cases, this improved algorithm has important practical significance. In this paper, the coaxial phase contrast imaging experiments of standard physical samples and mouse brain samples are carried out at Shanghai Light Source, and then the phase recovery reconstruction is done by using the phase recovery algorithm proposed in this paper. The experimental results show that the coaxial phase contrast imaging can better distinguish different components of soft tissue, and there is a greater degree of differentiation between the reconstruction values of different tissues, so more information of tissue structure can be obtained than that of absorption imaging. The experimental results show the great potential of coaxial phase contrast imaging in the imaging of biological soft tissue.
【學(xué)位授予單位】：上海交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：R811;O434.1
【參考文獻】
相關(guān)期刊論文 前6條
1 高鴻奕,陳建文,謝紅蘭,朱化風(fēng),李儒新,徐至展,朱佩平,袁清習(xí),田玉蓮,黃萬霞,王[鐫
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