本文選題：醫(yī)學(xué)影像處理與分析 + 分割��； 參考：《電子科技大學(xué)》2016年碩士論文

【摘要】：隨著醫(yī)療成像設(shè)備突飛猛進(jìn)的發(fā)展,針對(duì)不同成像設(shè)備的圖像處理算法也層出不窮。為了充分利用已有算法,避免重復(fù)開發(fā),一些國(guó)內(nèi)外研究機(jī)構(gòu)研發(fā)了醫(yī)學(xué)影像處理與分析軟件平臺(tái)�，F(xiàn)有的醫(yī)學(xué)影像處理與分析軟件平臺(tái)在特定領(lǐng)域已經(jīng)取得了巨大的成功,但是還存在如下不足:一些功能強(qiáng)大的醫(yī)學(xué)影像處理與分析綜合平臺(tái)需要配套醫(yī)療設(shè)備或特殊硬件才能運(yùn)行,價(jià)格昂貴,不利于學(xué)習(xí)和在醫(yī)學(xué)領(lǐng)域的普遍使用;開源框架的軟件平臺(tái)二次開發(fā)學(xué)習(xí)成本過高,這主要是由于其依賴的開源軟件庫(kù)過于龐大和復(fù)雜造成;由于醫(yī)學(xué)影像數(shù)據(jù)本身的復(fù)雜性,使得現(xiàn)有軟件平臺(tái)的專業(yè)性太強(qiáng),通用性不足,使用不便。本文的設(shè)計(jì)目標(biāo)是在Windows操作系統(tǒng)下集成常用的醫(yī)學(xué)影像處理與分析算法,以減輕算法研究者在算法工具使用上的學(xué)習(xí)成本,使得他們能夠?qū)Ｗ⒂谛滤惴ǖ脑O(shè)計(jì)和對(duì)比分析。論文的主要內(nèi)容如下:1、醫(yī)學(xué)影像處理與分析算法平臺(tái)的設(shè)計(jì)。該算法平臺(tái)劃分為三層:第一層,底層,基于VTK、ITK、FSL等成熟開源算法庫(kù)構(gòu)建;第二層,中間層,將底層算法庫(kù)中關(guān)于醫(yī)學(xué)影像格式轉(zhuǎn)換、濾波、配準(zhǔn)、分割和三維重建的算法按照統(tǒng)一的圖像讀寫接口封裝,以便于應(yīng)用層的調(diào)用;第三層,應(yīng)用層,把中間層提供的算法按照一定的規(guī)則組合、連接,設(shè)計(jì)了圖像格式轉(zhuǎn)換、配準(zhǔn)與分割、顯示三個(gè)交互模塊。2、醫(yī)學(xué)影像處理與分析軟件的實(shí)現(xiàn)。依據(jù)醫(yī)學(xué)影像處理與分析算法平臺(tái)的設(shè)計(jì),對(duì)底層ITK和VTK算法庫(kù)中相關(guān)算法進(jìn)行了封裝,將FSL算法庫(kù)中關(guān)于腦部影像配準(zhǔn)與分割的功能模塊移植到了Windows操作系統(tǒng)下運(yùn)行,把MATLAB環(huán)境下運(yùn)行的腦部海馬體三維分割算法集成到了算法平臺(tái)中,所有算法均按照中間層圖像讀寫接口的設(shè)計(jì)規(guī)則進(jìn)行封裝。軟件中實(shí)現(xiàn)了應(yīng)用層的三個(gè)交互模塊:第一個(gè),圖像格式轉(zhuǎn)換模塊,實(shí)現(xiàn)了DICOM切片序列轉(zhuǎn)換為三維NIf TI文件、三維NIfTI文件重切片為DICOM序列等格式轉(zhuǎn)換功能;第二個(gè),配準(zhǔn)與分割模塊,實(shí)現(xiàn)了FLIRT(腦部影像線性配準(zhǔn))、FIRST(腦部影像興趣區(qū)域分割)、BET(腦組織提取)、HST(腦部海馬體分割)四個(gè)算法;第三個(gè),顯示模塊,實(shí)現(xiàn)了醫(yī)學(xué)影像二維顯示和三維重建,二維顯示支持興趣區(qū)域勾畫,三維重建支持面繪制、網(wǎng)格繪制和體繪制,體繪制中支持標(biāo)簽圖像的疊加顯示。3、軟件功能測(cè)試。使用CT、MRI影像測(cè)試了格式轉(zhuǎn)換模塊、配準(zhǔn)與分割模塊、顯示模塊,驗(yàn)證了這三個(gè)模塊的正確性。特別地,使用ADNI數(shù)據(jù)庫(kù)中的腦部MRI影像對(duì)FIRST算法在Windows和Linux操作系統(tǒng)下分別進(jìn)行了18組實(shí)驗(yàn),根據(jù)Precision相似測(cè)度對(duì)FIRST算法分割結(jié)果進(jìn)行比較,兩個(gè)操作系統(tǒng)下的分割結(jié)果沒有明顯差別,證明了移植后的FIRST算法能夠正確運(yùn)行。
[Abstract]:With the rapid development of medical imaging equipment, image processing algorithms for different imaging equipment are emerging in endlessly. In order to make full use of existing algorithms and avoid repeated development, some domestic and foreign research institutions have developed medical image processing and analysis software platform. The existing software platform for medical image processing and analysis has achieved great success in specific fields. But there are the following shortcomings: some powerful medical image processing and analysis platform needs medical equipment or special hardware to run, the price is expensive, which is not conducive to learning and widely used in the field of medicine; The cost of secondary development of open source framework software platform is too high, which is mainly due to the huge and complex open source software library it relies on, and the complexity of medical image data makes the existing software platform too professional. The generality is not enough, the use is inconvenient. The design goal of this paper is to integrate common medical image processing and analysis algorithms under the Windows operating system, so as to reduce the learning cost of algorithm researchers in the use of algorithm tools, so that they can focus on the design and comparative analysis of new algorithms. The main contents of this paper are as follows: 1, the design of medical image processing and analysis algorithm platform. The algorithm platform is divided into three layers: the first layer, the bottom layer, based on VTKKITK / FSL and other mature open source algorithm library, the second layer, the middle layer, the bottom algorithm library about the medical image format conversion, filtering, registration, The algorithms of segmentation and 3D reconstruction are encapsulated according to the unified image reading and writing interface, so as to facilitate the call of the application layer, the third layer, the application layer, combines the algorithms provided by the middle layer according to certain rules, and designs the image format conversion. Registration and segmentation, display three interactive modules. 2, medical image processing and analysis software implementation. According to the design of medical image processing and analysis algorithm platform, this paper encapsulates the related algorithms in the underlying ITK and VTK algorithm library, and transplants the function module of brain image registration and segmentation in the FSL algorithm library to the Windows operating system to run. The 3D segmentation algorithm of brain hippocampus running in MATLAB environment is integrated into the algorithm platform, and all the algorithms are encapsulated according to the design rules of the middle layer image read-write interface. Three interactive modules of the application layer are implemented in the software: the first is the image format conversion module, which realizes the conversion function of DICOM slice sequence to 3D NIf TI file, 3D NIfTI file reslice to DICOM sequence and so on. In the module of registration and segmentation, four algorithms of FIRST (brain image linear registration) are implemented, and the third, display module, realizes two-dimensional display and 3D reconstruction of medical image. 2D display supports drawing of region of interest, 3D reconstruction support surface rendering, mesh rendering and volume rendering, and volume rendering supports superposition display of label image. The format conversion module, registration and segmentation module and display module are tested with CTT MRI image, and the correctness of the three modules is verified. In particular, using brain MRI images in ADNI database, 18 groups of experiments were carried out on FIRST algorithm under Windows and Linux operating system respectively, and the results of FIRST segmentation were compared according to Precision similarity measure. There is no obvious difference in the segmentation results between the two operating systems, which proves that the transplanted FIRST algorithm can run correctly.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP391.41

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本文編號(hào)：1839391