 |
|
|
|
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：113 、訪客IP：18.119.158.224
姓名 許銘允(Ming-Yun Hsu) 查詢紙本館藏 畢業系所 光電科學與工程學系 論文名稱 單光子放射顯微鏡系統之影像系統矩陣改良與反卷積算法改善解析度
(Improvement of the Imaging System Matrix and Resolution Enhancement by Using the Deconvolution Algorithm in Single Photon Emission Microscope)相關論文 檔案 [Endnote RIS 格式]
[相關文章]
[文章引用]
[完整記錄]
[館藏目錄]
至系統瀏覽論文 (2029-7-1以後開放)
摘要(中) 在核子醫學影像技術的臨床前小動物試驗中，若想使體積小的動物器官重建影像具備與人類器官重建影像同等的精確度，則必須使用比人類器官影像重建更高空間解析度的影像擷取設備。關於投影影像的擷取設備，此論文採用單光子放射顯微鏡系統(Single Photon Emission Microscope,SPEM)，該系統為單光子放射電腦斷層掃描系統(SPECT)的高空間解析度分支，所用設備包含了電子增益電荷耦合元件(EMCCD)、高質量光影像縮倍管、摻鉈碘化銫晶體 CsI(Tl)及七針孔式準直儀。
在電腦斷層掃描技術領域中為求得高品質的重建物體影像，需具備物空間與像空間的轉換關係矩陣，即高解析度且精確的影像系統矩陣。而本研究為建立更精確的影像系統矩陣，因此改善了本實驗室舊有的成像模型計算方法。
過去我們的實驗室致力於獲取 SPEM 的旋轉載物平台的空間關係幾何參數，為此進行了兩項實驗：幾何校正實驗和格點掃描實驗。經過兩項實驗後獲得了物空間範圍內各個位置點源的投影影像，通過分析這些點源的投影影像，我們可以獲得原物體空間的點響應函數，並將其簡化為二維高斯函數，其函數包括六項參數，六項參數分別為光通量、投影點的 x、y 質心座
標、投影點橢圓的主軸方向以及長軸與短軸的長度。將前述兩項實驗投影點vi的 x、y 座標用於幾何參數的擬合，取得空間座標的轉換關係參數，利用此參數進行全域優化，獲得全域座標系。
接著使用此座標系並結合前述之六項高斯參數、格點全域座標，首先進行針孔軸的擬合計算，於取得針孔軸向量之後，建立並改善過去實驗室的成像模型。建立了成像模型後利用此改良後模型建立不同格點間距的影像系統矩陣，並將其用於序列子集之期望值最大化演算法來進行影像重建以得到物體影像，並且為了提高影像重建的解析度及對比度，本研究於序列子集之期望值最大化演算法重建中及重建後分別對於物體重建的結果，皆應用移變點響應函數且使用反卷積演算法來進行去模糊演算，並且比較於影像重建演算法中及後進行去模糊演算的重建結果差異。摘要(英) In preclinical small animal experiments of nuclear medicine imaging technology, it is necessary to use imaging equipment with higher spatial resolution than that used for human organ imaging. The goal is to make the reconstructed images of small animal organs have the same precision as the reconstructed images of human organs. This thesis utilizes the Single Photon Emission Microscope (SPEM) as the imaging system to acquire projection images. SPEM is a specialized branch of the Single Photon Emission Computed Tomography (SPECT) with high spatial resolution. It contains a seven-pinhole collimator, a thallium-doped cesium iodide crystal CsI (Tl), an electrostatic de-magnifier tube, and an Electron-Multiplying Charge-Coupled Device (EMCCD).
To achieve high-quality reconstruction of object images in the field of computed tomographic technology, it requires a matrix that establishes the transformation relationship between the object space and the image space, that is, a high-resolution and accurate imaging system matrix. This study aims to establish a more accurate imaging system matrix by improving and optimizing the steps and calculation methods used in our laboratory′s previous imaging system
matrix.
In the past, our laboratory had focused on obtaining the geometric parameters between the detector, the translation stages, and the rotating platform for SPEM. For this purpose, two experiments were conducted: a Geometric Calibration experiment and a Grid-Scan experiment. After these two experiments, we obtained the projection images of point sources at various positions within the object space. By analyzing the projection images of these point sources, we got the point response functions of the object space and simplified them into two-dimensional Gaussian functions with six parameters. These six parameters are flux, x and y centroids of the point source projection, the principal axis angle of the ellipse-like projection image, and the length parameters of the major and minor axes. The x and y centroid coordinates were used to fit the geometric parameters between the detector, the translation stages, and the rotating platform for subsequently obtaining a global coordinate system.
Using this coordinate system in combination with the previously mentioned six Gaussian parameters and the global coordinates of the grid, we first calculated the pinhole-axis fitting. After obtained the pinhole-axis vectors, this study established and improved the previous imaging model from our laboratory. We then used this improved model to create imaging system matrices of different voxel spacings. These different matrices will be used in the Ordered-Subset
Expectation Maximization (OSEM) algorithm to reconstruct the object image. To enhance the resolution and contrast of the reconstructed object images, we applied the shift-variant point response functions and used the deconvolution algorithm during and after the OSEM reconstruction to perform deblurring calculations. Additionally, we compared the differences in reconstruction results between the original OSEM reconstruction, and the reconstructions with the deblurring algorithm during and after the OSEM reconstructions.關鍵字(中) ★ 單光子放射顯微鏡
★ 成像模型
★ 影像系統矩陣
★ 反卷積關鍵字(英) ★ SPEM
★ Imaging Model
★ Image System Matrix
★ Deconvolution論文目次 中文摘要 v
Abstract vii
致謝 ix
目錄 xi
圖目錄 xv
表目錄 xxii
第一章 緒論 1
1.1 研究背景 1
1.2 研究目的 3
1.3 論文架構 5
第二章 核子醫學影像儀器與原理 6
2.1 核子醫學影像 6
2.1.1 正子放射斷層掃描系統(Positron Emission Tomography, PET) 8
2.1.2 單光子放射電腦斷層掃描系統(Single-Photon Emission Computed Tomography, SPECT) 11
2.1.3 單光子放射顯微鏡系統(Single Photon Emission Microscope, SPEM) 16
2.2 準直儀(Collimator) 19
2.3 閃爍晶體偵測器(Scintillation Detector) 22
第三章 單光子放射顯微鏡之系統校正、影像重建及改善 28
3.1影像系統矩陣與高斯參數化 28
3.1.1影像系統矩陣(Image System Matrix, H Matrix) 28
3.1.2 格點掃描實驗(Grid-scan Experiment) 31
3.1.3 投影影像二維高斯函數參數化 32
3.1.4 幾何共線投影模型 34
3.2 系統與校正 36
3.2.1 實際單光子放射顯微鏡系統 37
3.2.2 初步校正(Preliminary Calibration) 40
3.2.3 幾何校正(Geometric Calibration) 45
3.2.4 簡化格點掃描實驗(Simplified Grid-scan Experiment) 48
3.2.5 全域優化(Global Optimization) 49
3.3 成像模型(Imaging Model) 51
3.3.1 針孔軸估算(Pinhole Axis Estimate) 53
3.3.2 通量模型(Flux Model) 55
3.3.3 寬度模型(Width Model) 58
3.3.4 主軸角度模型(Principle Angle Model) 62
3.4 影像重建演算法 64
3.4.1 最大可能性之期望值最大化演算法(Maximum-Likelihood Expectation Maximization, MLEM) 66
3.4.2 序列子集之期望值最大化演算法(Ordered-Subset Expectation Maximization, OSEM) 68
3.5 移變理查森-露西反卷積演算法(Shift-Variant Richardson-Lucy Deconvolution Algorithm, SV-RL) 70
3.5.1理查森-露西反卷積演算法(Richardson-Lucy Deconvolution Algorithm, RL) 70
3.5.2移變點擴散函數(Shift-Variant Point Spread Function, SV-PSF) 71
3.5.3移變點響應函數(Shift-Variant Point Response Function, SV-PRF)的重建方法 73
3.5.4演算流程 78
第四章 實驗過程與演算結果 81
4.1 系統校正與計算結果 81
4.1.1 幾何校正實驗 81
4.1.2 格點掃描實驗 82
4.1.3 全域優化與系統校正參數計算 84
4.2擬合並建立成像模型與影像系統矩陣 88
4.2.1 實際針孔軸估算(Pinhole Axis Estimation) 88
4.2.2 通量模型擬合 90
4.2.3 寬度模型擬合 98
4.2.4 主軸角度模型擬合 108
4.2.5 通量模型與寬度模型之比較與討論 116
4.2.6 建立影像系統矩陣 125
4.3 OSEM影像重建結果 127
4.3.1 解析度假體影像重建 127
4.3.2 OSEM影像重建結果的比較與討論 144
4.4理查森-露西演算法(Richardson-Lucy algorithm, RL)結果 145
4.4.1 移變點響應函數(Shift-variant Point Response Function)重建與擬合 145
4.4.2 移變點響應函數內插及外插 159
4.4.3 RL演算結果與討論 164
第五章 結論與未來展望 177
5.1 結論 177
5.2 未來展望 180
參考文獻 182參考文獻 [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] M. V. Green, J. Seidel, J. J. Vaquero, E. Jagoda, I. Lee, and W.C. Eckelman, “High resolution PET, SPECT and projection imaging in small animals,” Computerized Medical Imaging and Graphics, vol. 25, no. 2, pp. 79-86, 2001.
[3] A. Hasse, G. Landwehr, and E. Umbach, “Röntgen centennial: X-rays in Natural and Life Sciences,” World Scientific, Singapore, pp. 7-8, 1997.
[4] B. Y. Huang, System Calibration and Imaging Model Construction of Single Photon Emission Microscope, Master Thesis, National Central University, Taoyuan, Taiwan, 2018.
[5] M. N. Wernick, and J. N. Aarsvold, Emission Tomography: The Fundamentals of PET and SPECT, Elsevier Academic Press, London, 2004.
[6] G. L. Zeng, and J. R. Galt, “Analytic image reconstruction methods,” in Emission Tomography: The Fundamentals of PET and SPECT, M. N. Wernick and J. N. Aarsvold eds., pp. 127-152, Elsevier Academic Press, San Diego, CA, 2004.
[7] C. Y. Chen, Development of GPU-based Position Estimator and Image Reconstruction Algorithms for Micro-SPECT Systems, Master Thesis, National Central University, Taoyuan, Taiwan, 2014.
[8] R. Golestani, C. Wu, R. A. Tio, C. J. Zeebregts, A. D. Petrov, and F. J. Beekman, et al., “Small-animal SPECT and SPECT/CT: application in cardiovascular research,” European Journal of Nuclear Medicine and Molecular Imaging, vol. 37, pp. 1766-1777, 2010.
[9] M. A. D. Reis, J. Mejia, I. R. Batista, M. R. F. F. D. Barboza, and S. A. Nogueira, et al., “SPEM: A state-of-the-art instrument for high resolution molecular imaging of small animal organs,”SciELO Einstein (São Paulo), vol. 10, no. 2, pp. 209-215, 2012.
[10] J. Mejia, M. A. Reis, A. C. C. Miranda, I. R. Batista, and M. R. F. Barboza, et al.,“Performance assessment of the single photon emission microscope: high spatial resolution SPECT imaging of small animal organs,”SciELOBrazilian Journal of Medical and Biological Research, vol. 46, no. 11, pp. 936-942, 2013.
[11] L. J. Meng, N. H. Clinthorne, S. Skinner, R. V. Hay, and M. Gross, “Design and feasibility study of a single photon emission microscope system for small animal I-125 imaging,”IEEE Transactions on Nuclear Science, vol. 53, no. 3, pp. 1168-1178, 2006.
[12] K. V. Audenhaege, R. van Holen, S. Vandenberghe, C. Vanhove, S. D. Metzler and S. C. Moore, “Review of SPECT collimator selection, optimization and fabrication for clinical and preclinical imaging,” Medical Physics, vol. 42, no. 8, pp. 4796-813, 2015.
[13] A. P. Dhanasopon, C. S. Levin, A. M. K. Foudray, P. D. Olcott, J. A. Talcott, and F. Habte, “Scintillation crystal design features for a miniature gamma ray camera,”IEEE Nuclear Science Symposium Conference Record, vol. 5 pp. 1967-1971, 2003.
[14] M. A. Kupinski, and H. H. Barrett, Small-Animal SPECT Imaging, Springer, New York, 2005.
[15] C. Fiorini, A. Longoni, F. Perotti, C. Labanti, P. Lechner, and L. Strüder, “Gamma ray spectroscopy with CsI(Tl) scintillator coupled to silicon drift chamber,”IEEE Transactions on Nuclear Science, vol. 44, no. 6, pp. 2553- 2560, 1997.
[16] Available:http://www.ysctech.com/digital-microscope-CCD-camera-info.html
[17] L. J. Meng, “An intensified EMCCD camera for low energy gamma ray imaging applications,” IEEE Transactions on Nuclear Science, vol. 53, no. 4, pp. 2376-2384, August 2006.
[18] Available: https://www.teo.com.tw/products?product_id=1429
[19] H. H. Barrett, and K. J. Myers, Foundations of Image Science, Wiley Interscience, Hoboken, N. J., 2004.
[20] 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,” Elsevier Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, vol. 737, pp. 122-134, 2014.
[21] C. C. Wu, “Geometric Parameter Fitting and Imaging Model Improvement of Single Photon Emission Microscope,” Master Thesis, National Central University, Taoyuan, Taiwan, 2021.
[22] F. van der Have, B. Vastenhouw, M. Rentmeester, F. J. Beekman, “System calibration and statistical image reconstruction for ultra-high resolution stationary pinhole SPECT,” IEEE Transactions on Medical Imaging, vol. 27, no. 7, pp. 960-971, July 2008.
[23] Y. Wang, and B. M. W. Tsui, “Pinhole SPECT with different data acquisition geometries: usefulness of unified projection operators in homogeneous coordinates,” IEEE Transactions on Medical Imaging, vol. 26, no. 3, pp. 298-308, 2007.
[24] E. M. C. Revilla, System Calibration and Helical Reconstruction of Single Photon Emission Microscope, Master Thesis, National Central University, Taoyuan, Taiwan, 2018.
[25] L. A. Shepp, and Y. Vardi, “Maximum likelihood reconstruction for emission tomography,” IEEE Transactions on Medical Imaging, vol. 1, no. 2, pp. 113-122, 1982.
[26] H. M. Hudson, and R. S. Larkin, “Accelerated image reconstruction using ordered subsets of projection data,” IEEE Transactions on Medical Imaging, vol. 13, no. 4, pp. 601-609, 1994.
[27] D. S. Lalush, and B. M. Tsui, “Performance of ordered-subset reconstruction algorithms under conditions of extreme attenuation and truncation in myocardial SPECT,” Journal of Nuclear Medicine, vol. 41, no. 4, pp. 737- 744, 2000.
[28] 林煒翔，「單光子放射顯微鏡之針孔穿隧模擬與系統矩陣建立」，碩士論文，國立中央大學，民國112年。
[29] W. H. Richardson, “Bayesian-Based Iterative Method of Image Restoration*,” Journal of the Optical Society of America, vol. 62, no. 1, pp. 55- 59, 1972.
[30] L. B. Lucy,. “An iterative technique for the rectification of observed distributions,” The Astronomical Journal, vol. 79, no. 6, pp. 745-754, 1974.
[31] M. L. Jan, M. W. Lee, and H. M. Huang, “PRF reconstruction for Compton-based prompt gamma imaging,” Physics in Medicine & Biology, vol. 63, no. 3, pp. 035015, 2018.
[32] D. A. Fish, A. M. Brinicombe, E. R. Pike, and J. G. Walker, “Blind deconvolution by means of the Richardson–Lucy algorithm,” Journal of the Optical Society of America A, vol. 12, no. 1, pp. 58-65, 1995.
[33] S. M. Kim , et al.," Resolution recovery reconstruction for a Compton camera," Physics in Medicine & Biology, vol. 58, no. 9, pp.2823-2840, 2013.指導教授 陳怡君(Yi-Chun Chen) 審核日期 2024-7-29 推文 plurk
funp
live
udn
HD
myshare
netvibes
friend
youpush
delicious
baidu
網路書籤 Google bookmarks
del.icio.us
hemidemi
facebook
twitter
google
reddit