本文選題：meta分析　切入點：胰腺癌　出處：《電子科技大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：胰腺癌是一種常見的惡性程度很高的胰腺腫瘤,作為全球致死率最高的疾病之一,世界各國都在加大力度研究胰腺癌的預(yù)防、診斷、預(yù)后以及治療過程。CT在診斷胰腺癌、可切除性手術(shù)評估、胰腺癌分期方面有比較理想的效果,但是對于病灶較小的情況和較復(fù)雜的病變,CT的診斷效果就不盡如人意。MRI是CT之后在近年迅速發(fā)展起來較新的一項影像技術(shù),在胰腺癌的診斷方面表現(xiàn)出更好的效果,現(xiàn)在很多研究者認為MRI在診斷胰腺癌時優(yōu)于CT,MRI作為當(dāng)前胰腺疾病診斷的主要手段之一表現(xiàn)出很多優(yōu)點,尤其是結(jié)合DWI和MRCP技術(shù)其診斷效果超越了當(dāng)前其他診斷手段。MRI和CT技術(shù)作為診斷胰腺癌最常用的兩種影像技術(shù),其診斷效果一直被人們拿來對比,各種研究得出來的結(jié)果有很多不一致的地方,甚至結(jié)論完全相反,我們針對MRI和CT在胰腺癌診斷方面整合近年的研究做一個meta分析,以做出一個新的統(tǒng)一的結(jié)論,為胰腺癌診斷提供指導(dǎo)意見。在這篇meta分析中我們主要研究幾個方面的內(nèi)容。首先,對近十年來的MRI和CT診斷胰腺癌的文獻進行了全面的檢索,嚴格按照納入標準篩選所有可能相關(guān)的文獻,最后納入了一些高質(zhì)量論文作為后續(xù)研究數(shù)據(jù);其次根據(jù)數(shù)據(jù)選擇和提取標準提取了研究所需的所有指標和必要數(shù)據(jù),綜合分析得出了一個統(tǒng)一的結(jié)論;最后我們針對MRI和CT對胰腺癌診斷可能存在的影響因素進行了亞組分析,通過統(tǒng)計檢驗計算出其影響診斷準確率的顯著程度。meta分析結(jié)果顯示,MRI診斷胰腺癌的敏感性和CT相仿,但是MRI的特異性要明顯高于CT,診斷胰腺癌的時候MRI是個更好的診斷手段。雖然影像學(xué)高速發(fā)展給胰腺癌的診斷帶來極大的方便,但是對胰腺癌準確的進行診斷依然是一項難題,為了輔助影像科醫(yī)生診斷胰腺癌和減輕影像科醫(yī)生的閱片工作,本文隨后對胰腺癌MRI圖像進行了計算機輔助診斷研究,對比了SVM和LDA方法對胰腺癌、胰腺炎患者和正常人的分類準確率。這部分工作主要包含以下流程:在醫(yī)院采集患者數(shù)據(jù),根據(jù)專家指導(dǎo)進行感興趣區(qū)域提取并提取圖像特征,實現(xiàn)機器學(xué)習(xí)算法后對訓(xùn)練數(shù)據(jù)集進行分類器訓(xùn)練,對MRI圖像中胰腺疾病特征進行量化,完成人眼視覺特征到計算機數(shù)據(jù)特征的轉(zhuǎn)換,最后對未知胰腺疾病患者MRI數(shù)據(jù)進行分類,為臨床提供計算機輔助診斷服務(wù)。
[Abstract]:Pancreatic cancer is a common malignancy with high pancreatic cancer, as one of the highest rates of fatal diseases in the world, all the countries in the world in the diagnosis of prevention, strengthen the study of pancreatic cancer, prognosis and treatment of.CT in the diagnosis of pancreatic cancer, surgical resectability assessment, has the ideal effect of pancreatic cancer. But for the small lesions and complex lesions, the diagnostic effect of CT is not satisfactory after CT in.MRI is developed rapidly in recent years a new imaging technique, shows better effect in the diagnosis of pancreatic cancer, now many researchers believe that MRI is superior in the diagnosis of pancreatic cancer CT, MRI as one of the principal means to the diagnosis of pancreatic disease showed a lot of advantages, especially the combination of DWI and MRCP technology as the diagnostic results beyond the diagnosis of pancreatic adenocarcinoma is the most of the other diagnostic means of.MRI and CT Technology Two kinds of imaging techniques commonly used, its diagnosis result has been compared with the results of the study, all have a lot of inconsistencies, even the opposite conclusion, we focus on the MRI and CT in the diagnosis of pancreatic cancer and integration of recent research and analysis to make a meta, to make a new unified conclusion and provide guidance for the diagnosis of pancreatic cancer. In this article we mainly analyze meta several research contents. Firstly, for the past ten years, MRI and CT in the diagnosis of pancreatic cancer literature conducted a comprehensive search, in strict accordance with the inclusion criteria for screening all relevant documents, finally incorporated a number of high quality papers as the follow-up study data; secondly according to the data selection and extraction standard extract all the indicators required and necessary data, comprehensive analysis and draw a unified conclusion; finally we aimed at MRI and CT in pancreatic cancer The subgroup analysis of the factors affecting the diagnosis may exist, through statistical tests to calculate the degree of.Meta analysis and the accuracy of its diagnostic display, MRI diagnosis of pancreatic cancer and the sensitivity of CT is similar, but the specificity of MRI was higher than that of CT, when the MRI diagnosis of pancreatic cancer is a better diagnostic tool. Despite the rapid development of imaging brings great convenience for the diagnosis of pancreatic cancer, but the accurate diagnosis of pancreatic cancer is still a difficult problem, in order to assist doctors of Radiology Diagnosis of pancreatic cancer and reduce radiologists reading work, then carry out a research on computer aided diagnosis of pancreatic cancer MRI image, compared to SVM and the LDA method for pancreatic cancer, pancreatitis and normal classification accuracy. This work mainly includes the following processes: collecting patient data in the hospital, under the guidance of experts are interested in Region extraction and extraction of image features, to achieve machine learning algorithm on the training data set classifier training to quantify pancreatic disease characteristics of the MRI image, the conversion is complete the visual characteristics to the computer data characteristics, and finally classify unknown pancreatic disease MRI data, provide computer aided diagnosis for clinical service.

【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：R445.2;R735.9
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本文編號：1610456