【摘要】：螺旋CBCT當(dāng)前廣泛用于臨床檢測(cè)、射線(xiàn)探傷等行業(yè),隨著電子信息、傳感器的快速發(fā)展及應(yīng)用需求的提高,對(duì)其重建質(zhì)量、成像速度及資源消耗都提出了更高的要求。作為精確重建的Katsevich算法能夠保證成像質(zhì)量,但因計(jì)算復(fù)雜、成像時(shí)間長(zhǎng)限制了其應(yīng)用。Katsevich算法的各種軟硬件優(yōu)化方案不斷被提出,但仍然難以滿(mǎn)足實(shí)際應(yīng)用中的要求。GPU的硬件結(jié)構(gòu)決定了GPU的并行特點(diǎn)及超強(qiáng)的運(yùn)算性能,CUDA編程技術(shù)使GPU用于通用計(jì)算領(lǐng)域更加便捷,兩者給Katsevich算法并行加速提供了條件。在Katsevich算法實(shí)現(xiàn)多切片重建的過(guò)程中,反投影步驟是計(jì)算最復(fù)雜、資源消耗最大的步驟。本文在錐束覆蓋理論的基礎(chǔ)上,提出了一種基于相鄰切片旋轉(zhuǎn)對(duì)稱(chēng)性的反投影法。通過(guò)設(shè)定切片間距為射線(xiàn)源Z軸間距的整數(shù)倍,構(gòu)造出相鄰切片旋轉(zhuǎn)對(duì)稱(chēng)性。利用該性質(zhì),對(duì)當(dāng)前切片上待重建點(diǎn)的對(duì)應(yīng)的投影數(shù)據(jù)信息進(jìn)行平移和旋轉(zhuǎn)操作,可以得出新切片對(duì)應(yīng)的投影數(shù)據(jù)貢獻(xiàn)度。投影數(shù)據(jù)貢獻(xiàn)范圍使用判決邊界進(jìn)行判斷,繼而使用旋轉(zhuǎn)矩陣加速判決邊界計(jì)算。相比于PI線(xiàn)法,時(shí)間和空間復(fù)雜度都有降低。使用Matlab進(jìn)行了相關(guān)仿真分析并成功重建出清晰的切片影像,驗(yàn)證了算法的有效性。本文結(jié)合重建算法和GPU特點(diǎn),給出了優(yōu)化后的Katsevich算法的濾波和反投影子模塊的并行加速方案。在微分求導(dǎo)過(guò)程中合理組織線(xiàn)程塊,充分提高SP利用率,減少內(nèi)存訪(fǎng)問(wèn)沖突;在插值模塊中,使用常量?jī)?nèi)存存儲(chǔ)插值變換模板及插值系數(shù),常量?jī)?nèi)存的使用也加快了訪(fǎng)問(wèn)速度;在離散希爾伯特模塊,使用傅里葉變換對(duì)處理輸入實(shí)信號(hào)的卷積,減少計(jì)算量,使用CUFFT函數(shù)庫(kù)實(shí)現(xiàn)FFT變換對(duì);在反投影模塊,初始化判決邊界數(shù)組作為模板存放在全局內(nèi)存空間,待重建切片根據(jù)距初始切片的位置使用旋轉(zhuǎn)矩陣更新對(duì)應(yīng)的判決邊界數(shù)組,并且一個(gè)thread負(fù)責(zé)一列體素的重建。在保證重建質(zhì)量的前提下,相比于CPU重建,GPU重建實(shí)現(xiàn)了130倍左右的加速比。相比于PI線(xiàn)法反投影重建2563規(guī)模切片,本文提出的基于旋轉(zhuǎn)對(duì)稱(chēng)性的反投影不僅重建時(shí)間減少0.4秒,內(nèi)存消耗僅僅是三分之一。
[Abstract]:Spiral CBCT is widely used in clinical detection, ray flaw detection and other industries. With the rapid development of electronic information, sensors and application requirements, the reconstruction quality, imaging speed and resource consumption are higher requirements. As an accurate reconstruction algorithm, Katsevich algorithm can guarantee the imaging quality. However, due to the complexity of calculation and the long imaging time, various software and hardware optimization schemes of its application. Katsevich algorithm have been proposed continuously. However, it is still difficult to meet the requirements of practical applications. The hardware structure of .GPU determines the parallelism of GPU and the super performance of CUDA programming technology, which makes it more convenient for GPU to be used in the field of general computing. Both of them provide the conditions for the parallel acceleration of Katsevich algorithm. In the process of multi-slice reconstruction by Katsevich algorithm, the step of backprojection is the most complicated and the most resource consuming step. Based on the theory of cone beam covering, this paper presents an inverse projection method based on rotational symmetry of adjacent slices. The rotation symmetry of adjacent slices is constructed by setting the slice spacing as integral times of the Z axis spacing of the ray source. By using this property, the corresponding projection data information of the current slice to be reconstructed is translated and rotated, and the contribution of the projection data corresponding to the new slice can be obtained. The contribution range of the projection data is judged by the decision boundary, and then the calculation of the decision boundary is accelerated by the rotation matrix. Compared with Pi line method, the time and space complexity are reduced. The correlation simulation analysis with Matlab is carried out and the clear slice image is reconstructed successfully, which verifies the validity of the algorithm. Combined with the characteristics of reconstruction algorithm and GPU, this paper presents a parallel acceleration scheme for filtering and backprojection submodules of the optimized Katsevich algorithm. In the process of differential derivation, the thread blocks are reasonably organized, the SP utilization ratio is improved fully, and the memory access conflict is reduced. In the interpolation module, the constant memory is used to store the interpolation transform template and interpolation coefficient, and the constant memory usage also speeds up the access speed. In the discrete Hilbert module, Fourier transform is used to deal with the convolution of input real signal, the computation is reduced, and the CUFFT function library is used to realize the FFT transform pair. The initialized decision boundary array is stored in the global memory space as a template. The slice to be reconstructed updates the corresponding decision boundary array with the rotation matrix according to the position from the initial slice, and a thread is responsible for the reconstruction of a list of voxels. On the premise of guaranteeing the reconstruction quality, the acceleration ratio of CPU reconstruction is about 130times higher than that of CPU reconstruction. Compared with the Pi line method, the proposed backprojection based on rotation symmetry not only reduces the reconstruction time by 0.4 seconds, but also consumes only 1/3 memory.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類(lèi)號(hào)】：TP391.41

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本文編號(hào)：2198075