發(fā)布時間：2018-05-03 16:51

  本文選題：Matlab + GUI　； 參考：《電子科技大學》2013年碩士論文

【摘要】：近年來，隨著磁共振成像技術的迅速發(fā)展以及產(chǎn)品成本的下降，核磁共振成像儀開始在各大醫(yī)院及科研院校被逐步推廣。除臨床疾病診斷所需的檢查外，使用磁共振成像技術探測人腦功能以及結構也是當今神經(jīng)科學研究的熱點。對大腦功能及結構磁共振數(shù)據(jù)的研究不僅要求具備相關的物理學基礎，還要掌握必要的醫(yī)學知識，同時也需精通信號處理分析技術，這種多學科的交叉融合對研究者的科研素養(yǎng)提出了極高要求。 基于此，本文采用基于Matlab GUI的界面設計，發(fā)展了一個腦部磁共振數(shù)據(jù)統(tǒng)計分析系統(tǒng)。此系統(tǒng)涵蓋了從原始數(shù)據(jù)整理到圖像統(tǒng)計分析再到結果圖像輸出的一套完整流程。結合實際科研工作的需要，此系統(tǒng)采用的數(shù)據(jù)處理分析方法均為當今科學界公認的可靠而又先進的方法。同時系統(tǒng)采用基于Matlab GUI的界面設計，，其操作直觀簡便，讓使用者極易掌握。此系統(tǒng)大致分為以下幾個模塊： 1. DICOM數(shù)據(jù)整理。根據(jù)頭信息(.hdr）批量將DICOM文件改名,同時按掃描序列、日期、被試類型等進行歸類。 2. fMRI數(shù)據(jù)處理。對功能磁共振數(shù)據(jù)進行感興趣區(qū)（ROI）信號提取、全腦相關網(wǎng)絡、網(wǎng)絡間相關、功能連接密度等分析。 3.結構MRI數(shù)據(jù)處理。對DTI數(shù)據(jù)進行纖維束微結構信息獲取、全腦纖維束連接矩陣建立、網(wǎng)絡屬性計算、纖維束方向密度函數(shù)（ODF）圖分析等處理。 4.小工具。包括低頻成份頻譜分析、種子點優(yōu)秀程度判斷、全腦模板分割、去除模板散點等實用功能。 通過編排合理的界面將上述功能整合，形成了一套界面簡潔、操作方便、可靠度高的適用于科研的人腦MRI數(shù)據(jù)統(tǒng)計分析系統(tǒng)，具有較高的推廣價值。
[Abstract]:In recent years, with the rapid development of magnetic resonance imaging technology and the decline of product cost, nuclear magnetic resonance imager has been gradually popularized in various hospitals and scientific research institutions. In addition to the necessary examinations for the diagnosis of clinical diseases, magnetic resonance imaging (MRI) is also a hot topic in neuroscience. The study of functional and structural magnetic resonance data of the brain requires not only the relevant physical basis, but also the necessary medical knowledge, as well as a good command of signal processing and analysis techniques. This kind of multi-disciplinary cross-fusion has put forward the extremely high request to the researcher's scientific research accomplishment. Based on this, a statistical analysis system of brain magnetic resonance data is developed by using interface design based on Matlab GUI. The system covers a complete process from raw data collation, image statistical analysis to result image output. According to the need of scientific research, the data processing and analysis methods used in this system are recognized by the scientific community as reliable and advanced methods. At the same time, the system adopts interface design based on Matlab GUI, its operation is intuitionistic and simple, which makes the user easy to master. The system is broadly divided into the following modules: 1. DICOM data collation. The DICOM file was renamed in batches according to the header information, and classified according to the scanning sequence, date and type of the subject. 2. FMRI data processing The data of functional magnetic resonance (fMRI) were extracted from ROI, the whole brain correlation network, the correlation between networks and the density of functional connection were analyzed. 3. Structure MRI data processing. The DTI data were obtained from the microstructures of the fiber bundle, the whole brain fiber bundle connection matrix was established, the network attribute was calculated, and the fiber bundle direction density function (DDF) graph was analyzed. 4. Gadget. It includes low frequency component spectrum analysis, seed point excellent degree judgment, whole brain template segmentation, removal of template scattered points and other practical functions. By arranging a reasonable interface to integrate the above functions, a set of human brain MRI data statistical analysis system with simple interface, convenient operation and high reliability is formed, which has high popularizing value.
【學位授予單位】：電子科技大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：TP391.41;R310

【參考文獻】

相關期刊論文 前1條

1 梁夏;王金輝;賀永;;人腦連接組研究:腦結構網(wǎng)絡和腦功能網(wǎng)絡[J];科學通報;2010年16期

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