本文選題：正電子發(fā)射斷層掃描技術 + 主觀評價法��； 參考：《杭州電子科技大學》2017年碩士論文

【摘要】：正電子發(fā)射斷層掃描技術(Positron Emission Tomography,PET)是核醫(yī)學領域中一種先進的臨床檢查影像技術,可以準確地反映機體內(nèi)部的生理、生化變化,進入21世紀后更是迅猛發(fā)展,已成為目前癌癥的早期診斷和腦功能成像中非常重要的檢查手段。PET圖像質(zhì)量評估是PET成像中一個極為重要的方面,也是對PET成像系統(tǒng)參數(shù)進行優(yōu)化的關鍵步驟。主觀評價法(Human Observer)是目前評估圖像質(zhì)量的主要手段,但并不適用于系統(tǒng)參數(shù)優(yōu)化的研究,因為需要花費醫(yī)生大量的時間和精力,為了結(jié)果的客觀性需要多名醫(yī)生共同參與。數(shù)字觀察器(Numerical Observers)可以很好地克服這些缺點,被越來越多的應用于圖像質(zhì)量評估中。在眾多數(shù)字觀察器中,考慮到應用的普遍性,本文選擇通道化Hotelling觀察器(Channelized Hotelling Observer,CHO)作為PET圖像質(zhì)量評估的方法。論文第一部分首先介紹了目前常用的圖像質(zhì)量評估方法包括本文主要用到的數(shù)字觀察器CHO及其研究現(xiàn)狀、PET系統(tǒng)成像原理和圖像重建過程、以及影響重建圖像質(zhì)量的因素;然后介紹本文數(shù)據(jù)的獲取方式GATE(Geant4 Application for Tomographic Emission)仿真方法。論文第二部分應用CHO評估PET系統(tǒng)參數(shù)對圖像質(zhì)量的影響。影響PET圖像質(zhì)量的因素包括硬件參數(shù)和軟件參數(shù),其中硬件參數(shù)主要有晶體厚度和軸向視野(Axial Field of View,AFOV),軟件參數(shù)主要有濾波器和迭代次數(shù)。硬件參數(shù)晶體厚度、軸向視野(AFOV)對圖像質(zhì)量的影響:晶體厚度和軸向視野(AFOV)是硬件中兩個主要因素,厚度和AFOV的增加能增加系統(tǒng)靈敏度并改善圖像質(zhì)量,但是成本也會隨之提高,掃描速度會下降。經(jīng)過對靈敏度,掃描速度以及成本問題的綜合考慮,本文將軸向視野分別設置為201.6mm和403.2mm,晶體厚度分別設置為15mm和17.5mm。用CHO評估它們對圖像質(zhì)量的影響,得到的結(jié)果顯示晶體厚度一樣時,軸向視野為403.2mm的系統(tǒng)生成的PET圖像比軸向視野為201.6mm系統(tǒng)的清晰,軸向視野一樣時,晶體厚度為17.5mm的系統(tǒng)生成的PET圖像比晶體厚度為15mm系統(tǒng)的清晰。軟件參數(shù)濾波器、迭代次數(shù)對圖像質(zhì)量的影響:濾波器和迭代次數(shù)是經(jīng)常研究的兩個軟件參數(shù),它們的取值對圖像質(zhì)量的影響非常大,通常圖像質(zhì)量會隨著它們的參數(shù)值的增加先變好后變差,因此為了得到最好的圖像質(zhì)量,確定它們的最佳參數(shù)非常重要,CHO可以對圖像質(zhì)量進行量化從而選擇最佳參數(shù)。首先通過對圖像質(zhì)量、仿真時間等因素的綜合考慮選擇3min為最佳掃描時間。其次本文用到的濾波器為高斯濾波器和非局部均值(Non-Local Mean,NLM)濾波器,并將高斯參數(shù)σ分別設置為0.5、0.8、1.1、1.4、2.0、3.0、4.0,NLM參數(shù)f分別設置為0.5、0.7、0.9、1.2、2.0、3.0、4.0。通過CHO對它們進行優(yōu)化,并評估兩種濾波器在最佳參數(shù)下的濾波效果。結(jié)果表明σ=1.4和f=0.5為高斯濾波器和NLM濾波器的最佳參數(shù),而且NLM濾波器的濾波效果比高斯濾波器好。最后本文將迭代次數(shù)分別設置為1、2、3、4、6、8、10次,當?shù)螖?shù)變大,圖像變清晰,但是由于圖像中的噪聲也被放大,當超過某個值后,圖像因噪聲影響變模糊。為了得到最佳迭代次數(shù),本文用CHO對上述迭代次數(shù)對應的圖像進行評估,結(jié)果表明迭代次數(shù)為4次時,圖像質(zhì)量最好。仿真結(jié)果說明CHO可以用于評估PET系統(tǒng)參數(shù)對圖像質(zhì)量的影響,其對PET研制以及PET圖像的輔助診斷具有重要意義。本文的創(chuàng)新之處在于研究者們通過CHO計算AUC值可以定量的確定參數(shù),并且這是國內(nèi)首先開展采用CHO方法評估PET系統(tǒng)參數(shù)對圖像質(zhì)量影響的研究。
[Abstract]:Positron emission tomography (Positron Emission Tomography, PET) is an advanced clinical examination of nuclear medicine imaging technology, can accurately reflect the physiological and biochemical changes within the organism, after entering twenty-first Century is the rapid development, has become the current inspection methods of.PET image quality assessment is very important for early diagnosis and functional imaging of brain cancer which is a very important aspect in PET imaging, is also a key step for the optimization of PET imaging system parameters. The subjective evaluation method (Human Observer) is the main means of evaluating image quality, but is not suitable for the parameter optimization of the system, because the doctor needs to spend a lot of time and energy, in order to the objectivity of the results takes more than doctors to participate. The digital observer (Numerical Observers) can overcome these shortcomings, has been applied to more and more Image quality assessment. In many digital viewer, considering the universality of application, this paper selects the channel of Hotelling observer (Channelized Hotelling Observer, CHO PET) as a method of image quality assessment. The first part introduces the research status of CHO and the observer digital image quality assessment methods are used in this paper include. The principle of PET imaging and image reconstruction process, and the factors affecting the quality of the reconstructed image; then describes the data acquisition mode (GATE Geant4 Application for Tomographic Emission) simulation method. The second part CHO was used to evaluate the effect of PET system parameters on the image quality. The factors affecting the quality of PET image including hardware parameters and software parameters, including the hardware parameters include the crystal thickness and axial view (Axial Field of View, AFOV), the main parameters of the software The filter and the number of iterations. The hardware parameters of crystal thickness, axial view (AFOV) effect on image quality: crystal thickness and axial view (AFOV) are the two main factors in hardware, increase the thickness and AFOV can increase the sensitivity of the system and improve the image quality, but the cost will be increased, the scanning speed will drop after. The sensitivity, considering the scanning speed and cost problems, the axial field of view were set to 201.6mm and 403.2mm respectively, the crystal thickness is set to 15mm and 17.5mm. using CHO to evaluate their impact on image quality, the results showed the same crystal thickness, axial view PET 403.2mm image generation system than axial view the 201.6mm system is clear, the axial view as when the crystal thickness is PET 17.5mm image generation system than the crystal thickness of 15mm system clear. Software filter parameters, Diego Effect of number of image quality: filter and the number of iterations is two software parameters frequently studied, their influence on the image quality value is very large, usually the image quality will be increased with the increase of their parameter values becomes better then worse, so in order to get the best image quality, to determine the optimal parameters of them very important, CHO can quantify the image quality so as to choose the optimal parameters. Based on the image quality, considering the simulation time and other factors the choice of 3min is the best scan time. Then filter used in this paper for the Gauss filter and the non local means (Non-Local, Mean, NLM) filter, and Gauss parameters were set up 0.5,0.8,1.1,1.4,2.0,3.0,4.0, NLM parameters of F were set to 0.5,0.7,0.9,1.2,2.0,3.0,4.0. by CHO to optimize them, and evaluate the two kinds of filters under the best parameters of the filter Results. The results show that the best parameters =1.4 and f=0.5 for the Gauss filter and NLM filter, and the filtering effect of NLM filter Gauss filter. Than the number of iterations were set for 1,2,3,4,6,8,10 times, when the number of iterations becomes larger, the image becomes clear, but because of the noise in the image is magnified, when more than one value, because the influence of noise image blur. In order to get the optimal number of iterations, the image of the number of iterations corresponding with the CHO evaluation results show that the iterative number is 4 times, the best image quality. The simulation results indicate that CHO can be used to evaluate the effect on image quality parameters of PET system, which is of great significance to PET development and diagnosis PET images. The innovation of this paper lies in the researchers through the CHO AUC calculation parameters can be determined quantitatively, and this is the first to carry out using CHO Methods to evaluate the influence of PET system parameters on image quality.

【學位授予單位】：杭州電子科技大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP391.41;R817

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