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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 周呈霙(Cheng-Ying Chou) | |
| dc.contributor.author | Yi-Yen Chuo | en |
| dc.contributor.author | 卓奕諺 | zh_TW |
| dc.date.accessioned | 2021-06-08T04:31:16Z | - |
| dc.date.copyright | 2011-08-22 | |
| dc.date.issued | 2011 | |
| dc.date.submitted | 2011-08-17 | |
| dc.identifier.citation | Byunghyun, J., D. Kaeli, D. Synho, and H. Pien. 2009. Multi GPU implementation of iterative tomographic reconstruction algorithms. IEEE International Symposium on Biomedical Imaging. 185-188.
Cho, S., E. Pearson, D. Xia, X. Han, C.A. Pelizzari, and X. Pan. 2008. A preliminary study of intensity-weighted ROI imaging in cone-beam CT. 6913: 691325-7. Defrise, M., F. Noo, and H. Kudo. 2000. A solution to the long-object problem in helical cone-beam tomography. Physics in Medicine and Biology. 45: 623-643. Feldkamp, L.A., L.C. Davis, and J.W. Kress. 1984. Practical cone-beam algorithm. Journal of the Optical Society of America. 1(6): pp.612-619. Fessler, J.A., Iterative Methods for Image Reconstruction. 2006, EECS Department, The University of Michigan, ISBI Tutorial. Jia, X., Y. Lou, R. Li, J. Lewis, C. Men, X. Gu, W.Y. Song, and S.B. Jiang. 2010. GPU-based Fast Low Dose Cone Beam CT Reconstruction via Total Variation. International Journal of Radiation Oncology Biology Physics. 78(3, Supplement 1): S45-S45. Jia, X., Y. Lou, R. Li, W.Y. Song, and S.B. Jiang. 2010. GPU-based Fast Cone Beam CT Reconstruction from Undersampled and Noisy Projection Data via Total Variation. Medical Physics. 37: 1757-1760. Katsevich, A. 2002. Theoretically Exact Filtered Backprojection-Type Inversion Algorithm for Spiral CT. SIAM Journal on Applied Mathematics. 62(6): 2012-2026. Katsevich, A. 2004. An improved exact filtered backprojection algorithm for spiral computed tomography. Advances in Applied Mathematics. 32(4): 681-697. LaRoque, S.J., E.Y. Sidky, and X. Pan. 2007. Accurate image reconstruction from sparse data in diffraction tomography using a total variation minimization algorithm. Medical Imaging 2007. 6513: 651302. Lifeng, Y., Z. Yu, E.Y. Sidky, C.A. Pelizzari, P. Munro, and P. Xiaochuan. 2006. Region of interest reconstruction from truncated data in circular cone-beam CT. Medical Imaging, IEEE Transactions on. 25(7): 869-881. Magnusson, M., P.-E. Danielsson, and J. Sunnegardh, Handling of Long Objects in Iterative Improvement of Nonexact Reconstruction in Helical Cone-Beam CT, in IEEE Transactions on Medical Imaging. 2006. p. 935-940. Okitsu, Y., F. Ino, and K. Hagihara. 2010. High-performance cone beam reconstruction using CUDA compatible GPUs. Parallel Computing. 36(2-3): 129-141. Rudin, L.I., S. Osher, and E. Fatemi. 1992. Nonlinear total variation based noise removal algorithms. Physica D. 60(1-4): 259 - 268. Scherl, H., B. Keck, M. Kowarschik, and J. Hornegger. 2007. Fast GPU-Based CT Reconstruction using the Common Unified Device Architecture (CUDA). Nuclear Science Symposium Conference Record, 2007. NSS '07. IEEE. 6: 4464-4466. Seungryong, C., Y. Lifeng, C.A. Pelizzari, and P. Xiaochuan. 2006. Circular Cone-beam Micro-CT for Small Animal Imaging with Truncated Data. Nuclear Science Symposium Conference Record, 2006. IEEE. 5: 2889-2891. Sunnegardh, J., Iterative Filtered Backprojection Methods for Helical Cone-Beam CT, in Department of Electrical Engineering. 2009, Linkoping University: Linkoping. p. 1-168. Sunnegardh, J. and P.-E. Danielsson. 2008. Regularized iterative weighted filtered backprojection for helical cone-beam CT. Medical Physics. 35(9): 4173-4185. Tam, K.C. 1997. Cone Beam Imaging of a Section of a Long Object with a Short Detector. Information Processing in Medical Imaging. 1230: 525 - 530. Xing, Z., B. Junguo, E.Y. Sidky, C. Seungryong, Z. Peng, and P. Xiaochuan. 2007. GPU-based 3D cone-beam CT image reconstruction: application to micro CT. Nuclear Science Symposium Conference Record, 2007. NSS '07. IEEE. 5: 3922-3925. Xu, F., A. Khamene, and O. Fluck. 2009. High performance tomosynthesis enabled via a GPU-based iterative reconstruction framework. Physics of Medical Imaging. 7258: pp. 72585A-72585A-8. Xu, F. and K. Mueller. 2007. Real-time 3D computed tomographic reconstruction using commodity graphics hardware. Physics in Medicine and Biology. 52: 3405-3419. Yu, L., D. Xia, Y. Zou, X. Pan, C. Pelizzari, and P. Munro. 2005. Region of interest reconstruction from truncated data in circular cone-beam CT. 5747: 412-418. Zhao, X., J.-J. Hu, and P. Zhang. 2009. GPU-Based 3D Cone-Beam CT Image Reconstruction for Large Data Volume. Journal of Biomedical Imaging. 2009: 1-8. Zou, Y. and X. Pan. 2004. Exact image reconstruction on pi-line from minimum data in helical cone-beam CT. Physics in Medicine and Biology. 49(941-959). Zou, Y., D. Xia, and X. Pan. 2006. ROI image reconstruction for a circle-arc trajectory. 6142: 614228-5. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/22865 | - |
| dc.description.abstract | 螺旋錐束電腦斷層掃描為現今X光臨床診療最常使用的掃描模式，由於硬體設備的發展，現今偵測器擁有比以往更快速的資料擷取速率，為確保在多層掃描器上良好的資訊流暢度與偵測器效能，必須建立更快速的影像重建程序。本研究擬利用圖像處理器強大的平行運算能力，進行螺旋錐束電腦斷層描的影像重建加速，在圖像處理器的應用策略上，共享記憶體的同區塊資訊開放與無資料存取分支衝突、材質記憶體的快速內插法和快取特性等都將被套用在實驗方法中。另外，由於斷層掃描期間暴露在連續的輻射中，將增加癌症誘發的可能性，進而危害健康，因此成為近來重大議題。降低照射角度以及輻射能量等方法雖可直接減少對人體的危害，但這些方法所產生的掃描結果與品質通常無法為臨床診療所接受。本研究也將利用感趣區域與迭代重建等方式，在擁有較少投影資訊的情形下進行完整的影像重建，藉以達到削減輻射劑量之目的。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2021-06-08T04:31:16Z (GMT). No. of bitstreams: 1 ntu-100-R98631009-1.pdf: 1195679 bytes, checksum: ee58543739849e16fc27eafd8d98715b (MD5) Previous issue date: 2011 | en |
| dc.description.tableofcontents | 誌謝 i
摘要 ii Abstract iii 目錄 v 圖目錄 vii 表目錄 viii 第一章 緒論 1 1.1 前言 1 1.2 研究動機與目的 4 1.3 本文架構 5 第二章 文獻回顧 6 2.1 螺旋錐束電腦斷層掃描 6 2.2 圖像處理器在X光醫學影像之應用 8 2.3 ROI與TV的應用 10 2.4 螺旋錐束電腦斷層掃描之迭代運算 13 第三章 材料與方法 16 3.1 實驗設備 16 3.1.1 圖像處理器簡介 16 3.1.2 CUDA程式結構 18 3.2 實驗方法 19 3.2.1 三維影像FDK重建演算法應用 19 3.2.2 迭代方法 21 3.2.3 以ROI降低照射劑量 22 3.2.4 CUDA程式最佳化 23 3.2.5 整合性影像重建加速 27 第四章 結果與討論 29 4.1 圓形錐束電腦斷層掃描之重建結果 29 4.1.1 圖像處理器對FDK演算重建結果 29 4.1.2 圖像處理器對EM演算重建結果 30 4.1.3 圖像處理器對FDK與EM演算重建時間 31 4.2 螺旋錐束電腦斷層掃描影像重建 32 4.2.1 圖像處理器對Katsevich演算法重建結果 32 4.2.2 利用ROI演算法重建物體影像 33 第五章 結論與建議 35 5.1 結論 35 5.2 建議 35 參考文獻 36 | |
| dc.language.iso | zh-TW | |
| dc.title | 圖像處理器輔助螺旋錐束電腦斷層掃描之劑量削減與影像重建加速 | zh_TW |
| dc.title | Accelerating Image Reconstruction and Dose Reduction of Helical Cone-beam Computed Tomography Using Graphics Hardware | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 99-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 許靖涵,王偉仲 | |
| dc.subject.keyword | 螺旋錐束電腦斷層掃描,圖像處理器,劑量削減, | zh_TW |
| dc.subject.keyword | Helical cone-beam CT,graphics processing unit,dose reduction, | en |
| dc.relation.page | 38 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2011-08-17 | |
| dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
| dc.contributor.author-dept | 生物產業機電工程學研究所 | zh_TW |
| 顯示於系所單位： | 生物機電工程學系 | |
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