基於圖形處理器進行微單光子放射電腦斷層掃描系統 之位置估算與影像重建演算法開發

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：76

、訪客IP：18.222.146.130

姓名

陳承穎(Cheng-ying Chen) 查詢紙本館藏

畢業系所

光電科學與工程學系

論文名稱

基於圖形處理器進行微單光子放射電腦斷層掃描系統之位置估算與影像重建演算法開發
(Development of GPU-based Position Estimator and Image Reconstruction Algorithms for Micro-SPECT Systems)

相關論文

★ 以GATE模型及系統矩陣演算法重建SPECT螺旋影像	★ LED檯燈視覺舒適度研究
★ 表面電漿共振系統之相位擷取與分析	★ 人眼眼球模型與視覺表現之模擬分析研究
★ 白光LED之視覺生理效應評估	★ 不同色溫螢光燈用於辦公室照明之視覺效應研究
★ 表面電漿共振儀之動態相位偵測技術與微量生物分子檢測應用	★ 二次通過成像架構量測人眼的光學系統品質
★ 週期性奈米金屬結構對拉曼散射訊號增強之研究	★ 日眩光要因分析研究
★ 非球面檢測之迭代相移干涉與子孔徑相位接合演算法開發	★ 應用可容忍隨機位移之相移干涉術於相位式表面電漿共振系統之穩定度增進
★ 以偵測任務及系統效能評估找尋多針孔微單光子放射電腦斷層掃描系統之最佳化配置	★ 結合表面電漿共振及溫度控制於免疫球蛋白鍵結之檢測分析
★ 以二次通過成像量測架構及降低誤差迭代演算法重建人眼之點擴散函數	★ 多陽極光電倍增管閃爍相機之訊號讀出系統與高效最大可能性位置估算演算法開發

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

基於現代的單光子放射電腦斷層掃描系統求精於成像程序的速度和解析度的提升，本論文將圖形處理器(Graphics Processing Unit, GPU)應用於伽瑪射線位置估算和斷層掃描影像重建演算法。
位置估算演算法由最大可能性值估算法(Maximum-Likelihood Estimator)配合多變數常態分佈模型(Multivariate Normal Model)建立，並且利用截尾重心法配合收縮格點尋找法(Truncated Center of Gravity + Contracting Grid Search)，快速而準確的估算每一筆伽瑪射線事件的發生位置，一秒可估算400,000筆事件，且保有良好的準確率。利用位置估算法及規則格點圖像(Regular Grid Pattern)檢視所開發之伽瑪相機解析度，初步得知相機解析度至少可優於2 mm。
斷層掃描影像重建使用序列子集之期望值最大化演算法(Order Subset Expectation Maximization, OSEM)，且將動態運算(On The Fly Computation)應用在緻密立體像素格點之影像系統矩陣作正向投影與反向投影，快速地重建出高解析度之三維立體影像;使用數百萬個立體像素之影像系統矩陣進行三維影像重建僅需要數分鐘，達到高效率的成像程序。

摘要(英)

The aim of this study is to achieve fast image processing for a micro-SPECT system. Iterative algorithms are developed with powerful graphics processing units (GPUs) to perform position estimations and tomographic reconstructions.
The position estimator is constructed with the maximum-likelihood principle and the multivariate normal model. By using the truncated center of gravity combined with contracting grid search (TCOG-CGS), the algorithm can estimate the positions of gamma ray events rapidly and accurately. The processing speed is about 400,000 events per second for a gamma camera of 49 × 49 pixels with 1 mm pixel width. Also, the camera resolution is visualized by a regular grid pattern and the 2 mm grid spacing is resolvable.
For tomographic reconstructions, the ordered-subset expectation maximization (OSEM) algorithm is implemented with an imaging system matrix containing millions of voxels. To solve the memory storage issues, we bring in the concept of on-the-fly computation to the forward projection and backward projection of imaging system matrix. The GPU-based algorithm can reconstruct the 3D image with several millions of voxels in a few minutes, and is 19 times faster than the CPU-based algorithm.

關鍵字(中)

★ 圖形處理器
★ 最大可能性值估算法
★ 截尾重心法
★ 收縮格點尋找法
★ 序列子集之期望值最大化演算法
★ 動態運算

關鍵字(英)

★ GPU
★ Maximum-likelihood Estimator
★ Truncated Center of Gravity
★ Contracting Grid Search
★ Order Subset Expectation Maximization
★ On The Fly Computation

論文目次

中文摘要 i
Abstract ii
誌謝 iii
目錄 iv
圖目錄 vii
表目錄 xiii
第一章緒論 1
1.1 前言 1
1.2 研究目的 1
1.3 文獻回顧 2
1.4 論文架構 3
第二章研究背景之基本理論 5
2.1 核子醫學影像 5
2.1.1 正子放射斷層掃描系統(PET) 5
2.1.2 單光子放射電腦斷層掃描系統(SPECT) 7
2.2 伽瑪射線偵測器(Gamma Camera) 10
2.2.1 偵測器元件與物理特性 10
2.2.2 位置估算方法 15
2.3 影像重建演算法 17
2.3.1 最大可能性之期望值最大化演算法(Maximum Likelihood Expectation Maximization, MLEM) 19
2.3.2序列子集之期望值最大化演算法(Order Subset Expectation Maximization, OSEM) 22
2.4平行運算(Parallel Computing)之背景與介紹 24
2.4.1圖形處理器(Graphics Processing Unit, GPU) 25
2.4.2 統一計算架構(Compute Unified Device Architecture, CUDA) 28
2.4.3 加速程式庫(Thrust Library) 34
2.4.4 NVIDIA Tesla c2075 35
第三章位置估算方法運算平行化 37
3.1 偵測器平均響應函數(Mean Detector Response Function, MDRF) 37
3.1.1 實驗架構 37
3.1.2 儀控程式與訊號擷取 40
3.1.3偵測器平均響應函數之計算處理 42
3.2 GPU應用於伽瑪射線(Gamma-ray)位置估算 49
3.2.1 位置估算方法 50
3.2.2 位置估算方法之核心函數(Kernel Function) 56
3.2.3 CPU版本與GPU版本之效能比較 61
3.2.4 Flood Image和Grid Pattern 65
第四章影像重建演算法運算平行化 77
4.1 影像系統矩陣 77
4.2 GPU應用於影像重建演算法 81
4.2.1 動態運算(On The Fly Computation)應用於影像重建演算法 82
4.2.2 正向投影(Forward Projection)之核心函數(Kernel Function) 85
4.2.3 反向投影(Backward Projection)之核心函數(Kernel Function) 90
4.2.4 CPU版本與GPU版本之效能比較 93
第五章結論與未來展望 105
參考文獻 107

參考文獻

[1] S. R. Cherry and S. S. Gambhir, “Use of positron emission tomography in animal research,” ILAR Journal, vol. 42, no. 3, pp. 219-232, 2001.
[2] P. D. Acton and H. F. Kung, “Small animal imaging with high resolution single photon emission tomography,” Nucl. Med. Biol., vol. 30, no. 8, pp. 889-895, 2003.
[3] B. M. W. Tsui, Y. C. Wang, B. C. Yoder and E. C. Frey, “MICRO- SPECT,” Bio. Imag. IEEE Symp. pp. 373-376, 2002.
[4] F. Xu and K. Mueller, “Accelerating popular tomographic reconstruction algorithms on commodity PC graphics hardware,” IEEE Trans. Nucl. Sci., vol. 52, no. 3, pp. 654-663, 2005.
[5] B. Bai and A. M. Smith, “Fast 3D iterative reconstruction of PET images using PC graphics hardware,” IEEE Nucl. Sci. Symp. Conf. Rec. vol. 5, pp. 2787-2790, 2006.
[6] F. Alhassen, K. Sangtaek, G. Sayre, J. Bowen, R. Gould, Y. Seo, H. Kudrolli, B. Singh and V. Nagarkar, “Ultrafast multipinhole single photon emission computed tomography iterative reconstruction using CUDA,” IEEE Nucl. Sci. Symp. Med. Imaging Conf. Rec. pp. 2558-2559, 2011.
[7] B. W. Miller, R. Von Holen, H. H. Barrett and L. R. Furenlid, “A system calibration and fast iterative reconstruction method for next-generation SPECT imagers,” IEEE Trans. Nucl. Sci., vol. 59, no. 5, pp. 1990-1996, 2012.

[8] L. Caucci‚ Task Performance with List-Mode Data‚ PhD dissertation, University of Arizona, 2012.
[9] Y. H. Chung, Y. Choi, T. Y. Song, J. H. Jung, G. Cho, Y. S. Choe, K.
H. Lee, S. E. Kim, and B. T. Kim, “Evaluation of maximum-likelihood
position estimation with Poisson and Gaussian noise models in a small
gamma camera,” IEEE Trans. Nucl. Sci., vol. 51, no. 1, pp. 101-104, 2004.
[10] Y. C. Chen, System Calibration and Image Reconstruction for a New Small-Animal SPECT System, PhD dissertation, University of Arizona, 2006.
[11] J. Y. Hesterman, L. Caucci, M. A. Kupinski, H. H. Barrett, L. R. Furenlid, “Maximum-likelihood estimation with a contracting-grid search algorithm,” IEEE Trans. Nucl. Sci., vol. 57, no.3, pp. 1077-1084, 2010.
[12] Available: http://www.reak.bme.hu/Wigner_Course/2004/WignerManuals/Bratislava/Detectors.htm
[13] Available: http://zh.wikipedia.org/wiki/File:Photomultipliertube.svg
[14] Available: http://www.hamamatsu.com/us/en/product/category/3100/3002/H8500C/index.html
[15] W. C. J. Hunter, Modeling Stochastic Processes in Gamma-Ray Imaging Detectors and Evaluation of a Multi-Anode PMT Scintillation Camera for Use with Maximum-Likelihood Estimation Methods, PhD dissertation, University of Arizona, 2007.

[16] H. H. Barrett, “Detectors for Small-Animal SPECT Ⅱ,” in Small- Animal SPECT Imaging, M. A. Kupinski and H. H. Barrett eds., pp. 65-66, Springer, New York, NY, 2005.
[17] L. A. Shepp and Y. Vardi, “Maximum likelihood reconstruction for emission tomography,” IEEE Trans. Med. Imag., vol. 1, no. 2, pp.113-122, 1982.
[18] H. H. Barrett and K. J. Myers, Foundations of Image Science, Wiley-Interscience, Hoboken, NJ, pp.801-1000, 2004.
[19] H. M. Hudson and R. S. Larkin, “Accelerated image reconstruction using ordered subsets of projection data,” IEEE Trans. Med. Imag., vol. 13, no. 4, pp.601-609, 1994.
[20] D. S. Lalush and B. M. W. Tsui, “Performance of ordered-subset reconstruction algorithms under conditions of extreme attenuation and truncation in myocardial SPECT,” J. Nucl. Med., vol. 41, no. 4, pp. 737-744, 2000.
[21] 林俊淵等編著，CUDA輕鬆上手新世代GPU應用技術，松崗資訊股份有限公司，新北市，民國一百年七月
[22] NVIDIA CUDA C Programming Guide PG-02829-001_v5.5, July 2013.
[23] NVIDIA Thrust Quick Start Guide DU-06716-001_v5.5, July 2013.
[24] Available: http://en.wikipedia.org/wiki/Nvidia_Tesla

[25] Y. L. Lee, Development of Compact Readout Electronics and Efficient Maximum Likelihood Position Estimator for a Multi-Anode-PMT Scintillation Camera, Master thesis, National Central University, 2013.
[26] R.Wojcik, S. Majewski, D. Steinbach and A.G. Weisenberger, “High spatial resolution gamma imaging detector based on 5” diameter R329 2 hamamatsu PSPMT,” IEEE Trans. Nucl. Sci., vol. 45, no.3, pp. 487-491, 1998.
[27] NEMA Standards Publication NU 1-2007, “Performance Measurements of Gamma Cameras,” National Electrical Manufacturers Association, Rosslyn, VA, 2007.
[28] M. W. Lee and Y. C. Chen, “Rapid construction of pinhole SPECT system matrices by distance-weighted Gaussian interpolation method combined with geometric parameter estimations,” Nucl. Instrum. Methods Phys. Res. A., vol. 737, pp. 122-134, 2014.
[29] Y. Wang and B. M. W. Tsui, “Pinhole SPECT with Different Data Acquisition Geometries: Usefulness of Unified Projection Operators in Homogeneous Coordinates," IEEE Trans. Med. Imag., vol. 26, no. 3, pp. 298-308, 2007.
[30] W. T. Lin, Configuration Optimization for Multi-pinhole Micro-SPECT System by Detection Tasks and System Performance Evaluations, Master thesis, National Central University, 2013.

指導教授

陳怡君(Yi-chun Chen)

審核日期

2014-8-18

推文