本文選題：核磁共振圖像 + 心肌灌注��； 參考：《上海交通大學(xué)》2014年碩士論文

【摘要】：隨著生活節(jié)奏的不斷加快，心臟疾病的發(fā)病率在近20年中不斷增高，心血管疾病已成為死亡率最高的疾病之一。核磁共振技術(shù)的發(fā)展與成熟為心血管疾病的診斷和治療提供了重要的影像依據(jù)，也使心肌灌注的定量分析成為可能，而針對心肌灌注核磁共振圖像的研究對于指導(dǎo)心血管疾病的治療和預(yù)后判斷有重要意義。其中，心肌灌注核磁共振圖像的定量分析，是計算機輔助心血管疾病診斷和預(yù)后的重要基礎(chǔ)。 心肌灌注核磁共振圖像定量分析傳統(tǒng)上采用的是半定量的方法，以心肌壁造影劑充盈速度曲線得到的若干參數(shù)作為分析對象，而沒有考慮左心室中造影劑的充盈速度對于心肌壁造成的影響。因此，由于沒有去除這些干擾因素的影響，獲取的參數(shù)缺乏可靠的參照量對比，參數(shù)與血流量之間的關(guān)系都是通過經(jīng)驗觀測得到，進行量化分析不準(zhǔn)確。 為了提高準(zhǔn)確性，本文采用絕對定量分析方法，該方法的理論基礎(chǔ)是中心容積定律。該方法將左心室心肌灌注過程作為一個動態(tài)系統(tǒng)考慮，以左心室內(nèi)造影劑的灌注速度作為輸人，左心室心肌灌注殘留造影劑量作為輸出，左心室心肌灌注動態(tài)過程的數(shù)學(xué)模型作為需要測定或辨識的系統(tǒng)。首先對臨床采集的心肌灌注核磁共振圖像進行插值放大。然后進行圖像配準(zhǔn)，并采用平均濾波的方法對圖像的偽影和噪聲進行處理，獲得心肌灌注信號強度曲線以及左心室灌注信號強度曲線。隨后將灌注曲線進行解耦，建立基于相關(guān)數(shù)學(xué)模型的傳遞函數(shù)，也稱為剩余函數(shù)，并利用非線性優(yōu)化方法對數(shù)學(xué)模型進行參數(shù)辨識。 剩余函數(shù)的擬合又是絕對定量分析的關(guān)鍵，有人采用樣條模型，可以對剩余函數(shù)進行很好的擬合，但是樣條模型的參數(shù)太多，不容易對參數(shù)進行比較和分析。也有人使用Fermi模型來擬合剩余函數(shù)，但是參數(shù)不具有實際的物理意義。本文采用了指數(shù)模型對剩余函數(shù)進行擬合，指數(shù)模型帶有兩個參數(shù)，不但減少了參數(shù)的數(shù)量，而且模型參數(shù)具有更多的物理意義。本文對指數(shù)模型參數(shù)進行了分析和比較，通過和傳統(tǒng)的半定量方法的對比分析了指數(shù)模型的參數(shù)穩(wěn)定性。本文也通過比較正常人和非正常人之間的參數(shù)分析了基于指數(shù)模型定量方法對于臨床輔助診斷的意義。實驗證明，經(jīng)本文提出的方法具有良好的可靠性，能為醫(yī)生判斷心肌的狀態(tài)提供依據(jù)。在臨床診斷和治療中有臨床應(yīng)用價值。 本文根據(jù)臨床中對心肌灌注核磁共振圖像分析的需求，設(shè)計了相關(guān)定量分析軟件。軟件的輸入為臨床采集的心肌灌注核磁共振數(shù)據(jù)文件，輸出為定量分析參數(shù)的圖形界面。軟件主要由五個模塊組成：DICOM文件解析，，圖像配準(zhǔn)，圖像處理，參數(shù)辨識，用戶界面等。軟件設(shè)計框架基于MFC，采用C++和MATLAB混合編程的方法，以眼圖和數(shù)據(jù)相結(jié)合的直觀形式為醫(yī)生提供病人診斷信息。
[Abstract]:With the rapid pace of life, the incidence of heart disease has been increasing in the past 20 years, and cardiovascular disease has become one of the highest mortality diseases. The development and maturity of nuclear magnetic resonance technology provide important imaging basis for the diagnosis and treatment of cardiovascular disease, and make the quantitative analysis of myocardial perfusion possible. The study of myocardial perfusion MRI is of great significance in guiding the treatment and prognosis of cardiovascular diseases. The quantitative analysis of myocardial perfusion MRI is an important basis for computer aided diagnosis and prognosis of cardiovascular diseases. The quantitative analysis of myocardial perfusion MRI is a semi-quantitative method, and some parameters obtained from the filling velocity curve of myocardial contrast medium are taken as the analysis object. The effect of the filling velocity of contrast agent on myocardial wall was not taken into account. Therefore, because the influence of these interference factors is not removed, the obtained parameters are lack of reliable reference quantity contrast, the relationship between parameters and blood flow is obtained through empirical observation, and the quantitative analysis is not accurate. In order to improve the accuracy, an absolute quantitative analysis method is adopted, which is based on the central volume law. In this method, the left ventricular perfusion process is considered as a dynamic system, the perfusion rate of the left ventricular contrast agent is taken as the infusion rate, and the residual contrast agent quantity of the left ventricular perfusion is taken as the output. A mathematical model of the left ventricular perfusion process is used as a system to be measured or identified. Firstly, the myocardial perfusion MRI images collected by clinic were interpolated and amplified. Then the image registration is carried out, and the artifact and noise of the image are processed by the average filtering method, and the myocardial perfusion signal intensity curve and the left ventricular perfusion signal intensity curve are obtained. Then the perfusion curve is decoupled, and the transfer function based on the correlation mathematical model, also called residual function, is established. The nonlinear optimization method is used to identify the parameters of the mathematical model. The fitting of residual function is the key of absolute quantitative analysis. Some people can fit the residual function well by using spline model, but the parameters of spline model are too many to be compared and analyzed easily. Fermi model is also used to fit the residual function, but the parameters have no practical physical significance. In this paper, the exponential model is used to fit the residual function. The exponential model has two parameters, which not only reduces the number of parameters, but also has more physical significance. In this paper, the parameters of exponential model are analyzed and compared, and the parameter stability of exponential model is analyzed by comparing with the traditional semi-quantitative method. The significance of quantitative method based on exponential model for clinical diagnosis was also analyzed by comparing the parameters between normal and abnormal people. The experimental results show that the proposed method has good reliability and can provide a basis for doctors to judge the state of myocardium. It has clinical application value in clinical diagnosis and treatment. According to the requirement of myocardial perfusion MRI image analysis in clinic, a quantitative analysis software was designed. The input of the software is clinical myocardial perfusion nuclear magnetic resonance data file, and the output is the graphical interface of quantitative analysis parameters. The software consists of five modules: DICOM file analysis, image registration, image processing, parameter identification, user interface and so on. The software design framework is based on MFCs and adopts the method of C and MATLAB mixed programming to provide the diagnosis information for the doctor by the visual form of the combination of eye diagram and data.
【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】：2014
【分類號】：TP391.41;R445.2

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