發(fā)布時間：2018-05-20 04:46

  本文選題：X射線圖像分解 + 多能譜CT�。� 參考：《中北大學(xué)》2016年博士論文

【摘要】：X射線多譜CT成像相對于傳統(tǒng)單能假設(shè)的CT成像,其能譜信息更豐富,可依據(jù)能譜與衰減系數(shù)的多譜對應(yīng)性,實現(xiàn)檢測對象組分的有效區(qū)分,滿足新型材料、礦石深加工以及現(xiàn)代醫(yī)學(xué)中組分微觀結(jié)構(gòu)等定量化功能成像需求�，F(xiàn)有的雙能CT、光子計數(shù)型CT、能譜濾波分離多譜CT在時間和能譜分辨率上存在一定的局限性,而單色性較好的同步輻射CT為國家大科學(xué)裝置,共享面較寬,機時有限,限制了樣品測試實驗效率和規(guī)模。對此,論文在不改變常規(guī)CT成像系統(tǒng)物理組成的基礎(chǔ)上,研究連續(xù)譜X射線投影圖像能譜分離方法,期望分解所得投影的重建圖像能達到窄能譜CT圖像效果,從而在常規(guī)CT成像系統(tǒng)上實現(xiàn)組分有效區(qū)分,為微觀結(jié)構(gòu)的定量表征提供支撐。論文在研究X射線多譜衰減特性、多譜成像特點和單能假設(shè)CT重建的基礎(chǔ)上,分析了連續(xù)譜X射線投影序列分解的可行性,提出了基于盲源分離的多譜序列分離的CT成像方法。在此基礎(chǔ)上,采用非負矩陣分解方法,以誤差平方和最小為優(yōu)化準(zhǔn)則,構(gòu)建X射線圖像序列分解模型,并推導(dǎo)了求解算法。同時針對分解算法的局部收斂性問題,引入具有全局收斂的遺傳算法,提出了基于遺傳算法的X射線圖像序列非負矩陣分解方法,實現(xiàn)了多譜序列的有效分離,獲取的投影重建后圖像有窄能譜圖像特征。針對CT成像過程中散射因素的影響,利用分解殘差的局部方差和作為散射信號低頻特性的描述,以分解殘差的局部方差和最小為優(yōu)化準(zhǔn)則,改進了X射線圖像序列非負矩陣分解模型,提高了多譜序列的分離精度。針對盲源分離結(jié)果的無序性和窄譜投影的能量不確定性,利用光電效應(yīng)和康普頓效應(yīng)分解代替分解模型中的衰減系數(shù),提出了基于衰減系數(shù)分解的能譜校準(zhǔn)方法,實現(xiàn)了窄譜投影的能量指向;同時,考慮CT圖像序列表征問題,耦合多譜成像的物理先驗,利用基于DCM模型的窄譜CT序列融合算法,實現(xiàn)了組分的定量表征。論文在理論研究同時,進行實驗對比分析。實驗過程中,以硅鋁材質(zhì)構(gòu)成的圓柱體為對象,通過仿真與實驗相結(jié)合的方法,驗證了X射線投影序列分離的可行性,以及所提出的基于遺傳算法的X射線圖像序列非負矩陣分解方法、改進方法、以及能譜校準(zhǔn)和窄譜CT序列融合算法。結(jié)果表明,論文提出的基于盲源分離的多譜CT成像方法,可在不改變系統(tǒng)物理組成的基礎(chǔ)上,通過掃描模式和數(shù)據(jù)處理方法的創(chuàng)新,實現(xiàn)材料組分定量表征。這對提高實驗效率,降低成本,促進X射線多譜反演與定量檢測技術(shù)的發(fā)展,具有重要理論意義和應(yīng)用價值。
[Abstract]:Compared with conventional single-energy CT imaging, X-ray multispectral CT imaging has more information of energy spectrum. It can effectively distinguish the components of detecting objects according to the multi-spectral correspondence between energy spectrum and attenuation coefficient, and meet the requirements of new materials. Quantitative functional imaging needs such as ore deep processing and the microstructure of components in modern medicine. The existing dual-energy CTs, photon counting CTs and spectral filtering multi-spectral CT have some limitations in time and spectral resolution, while the monochromatic synchrotron radiation CT is a large national scientific device with a wide shared area and limited computer time. The efficiency and scale of the sample test are limited. Therefore, on the basis of not changing the physical composition of conventional CT imaging system, this paper studies the method of separating the energy spectrum of continuous spectrum X-ray projection image. It is expected that the reconstructed image can achieve the effect of narrow spectrum CT image. Thus, components can be effectively distinguished in conventional CT imaging system, which provides support for quantitative characterization of microstructure. On the basis of studying the characteristics of X-ray multispectral attenuation, multispectral imaging and single-energy assumption CT reconstruction, the feasibility of continuous spectral X-ray projection sequence decomposition is analyzed, and the CT imaging method based on blind source separation is proposed. On this basis, the non-negative matrix decomposition method is used to construct the X ray image sequence decomposition model with the minimum sum of error square as the optimization criterion, and the solution algorithm is derived. At the same time, aiming at the problem of local convergence of decomposition algorithm, a genetic algorithm with global convergence is introduced, and a non-negative matrix decomposition method of X-ray image sequence based on genetic algorithm is proposed, which realizes the effective separation of multi-spectral sequences. The reconstructed images are characterized by narrow-spectrum images. In view of the influence of scattering factors in CT imaging, the local variance of decomposition residuals is used as the description of the low frequency characteristics of scattering signals, and the local variance and minimum of decomposition residuals are taken as the optimization criteria. The nonnegative matrix decomposition model of X-ray image sequence is improved and the separation accuracy of multi-spectral sequence is improved. Aiming at the disorder of blind source separation results and the energy uncertainty of narrow spectral projection, a calibration method for energy spectrum based on attenuation coefficient decomposition is proposed, which is based on the decomposition of photovoltaic effect and Compton effect instead of the attenuation coefficient in the decomposition model. At the same time, considering the representation of CT image sequence, coupled with the physical priori of multispectral imaging, the fusion algorithm of narrow-spectrum CT sequence based on DCM model is used to realize the quantitative representation of components. At the same time, the thesis carries on the experiment contrast analysis in the theory research. In the course of experiment, the feasibility of separating X-ray projection sequence is verified by combining simulation and experiment with the cylinder made of silicon and aluminum. The non-negative matrix decomposition method of X-ray image sequence based on genetic algorithm, the improved method, and the fusion algorithm of spectral calibration and narrow-spectrum CT sequence are also presented. The results show that the proposed multispectral CT imaging method based on blind source separation can realize quantitative characterization of material components without changing the physical composition of the system and through the innovation of scanning mode and data processing methods. It is of great theoretical significance and application value to improve the experimental efficiency, reduce the cost and promote the development of X-ray multispectral inversion and quantitative detection technology.
【學(xué)位授予單位】：中北大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：TP391.41;O434.1
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本文編號：1913265