博碩士論文 102323105 詳細資訊




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:10 、訪客IP:3.129.253.65
姓名 嚴中成(Chung-chen Yan)  查詢紙本館藏   畢業系所 機械工程學系
論文名稱 三維近紅外光擴散光學斷層影像重建之數值計算研究
相關論文
★ TFT-LCD前框卡勾設計之衝擊模擬分析與驗證研究★ TFT-LCD 導光板衝擊模擬分析及驗證研究
★ 數位機上盒掉落模擬分析及驗證研究★ 旋轉機械狀態監測-以傳動系統測試平台為例
★ 發射室空腔模態分析在噪音控制之應用暨結構聲輻射效能探討★ 時頻分析於機械動態訊號之應用
★ VKF階次追蹤之探討與應用★ 火箭發射多通道主動噪音控制暨三種線上鑑別方式
★ TFT-LCD衝擊模擬分析及驗證研究★ TFT-LCD掉落模擬分析及驗證研究
★ TFT-LCD螢幕掉落破壞分析驗證與包裝系統設計★ 主動式火箭發射噪音控制使用可變因子演算法
★ 醫學/動態訊號處理於ECG之應用★ 光碟機之動態研究與適應性尋軌誤差改善
★ 具新型菲涅爾透鏡之超音波微噴墨器分析與設計★ 醫用近紅外光光電量測系統之設計與驗証
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]
  1. 本電子論文使用權限為同意立即開放。
  2. 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。
  3. 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) 本論文針對應用於乳癌檢測之近紅外光擴散光學斷層造影系統,發展三維組織光學係數影像重建演算法。組織光學重建以擴散方程式為模型,並將演算法分為前向計算與反向計算兩部分。在前向計算中使用有限元素法求解擴散方程式,以獲得在特定光源及光學係數分布下量測點的穿透光資訊。在逆向計算中為了藉由量測得的光資訊來重建模型中的光學係數分布使用牛頓法來疊代,並求出使量測與理論之光訊息差異最小化的光學係數分布,並加入Tikhonov正則化加強重建之結果。藉由設計不同仿乳房光學特性之模擬案例,驗證本研究演算法對於腫瘤之光學特性對比度、幾何尺寸、及腫瘤位置等特徵之計算辨識能力,並藉由一維剖面圖、重建影像之均方誤差來進行定量,以及腫瘤及背景組織特徵之解析度來評估影像重建結果。在採用直徑80 mm之圓柱體為幾何模型,並於光源調變頻率為100 MHz的設定下執行造影案例分析,根據結果可知,可以順利重建離心距離為0 mm,且對比度為2倍、直徑15 mm之腫瘤,但在直徑20 mm效果最好,,而對於腫瘤角度、深度位置特徵具辨識能力。在光學係數方面,當腫瘤光學係數對比度大於2.5倍時則重建結果可能會高估其對比度,而吸收係數及散射係數對比度差異高於1.5倍時則容易出現串擾現象。
摘要(英) This study focuses on developing three-dimensional image reconstruction algorithm of near-infrared diffuse optical tomography (NIR DOT) system for detecting breast cancer. The image reconstruction algorithm of DOT is based on the diffusion equation, and involves both the forward calculation and inverse reconstruction. The forward calculation solves the diffusion equation by using the finite element method (FEM) for calculating the distribution of transmitted light under the condition of presumed light source and optical coefficient (absorption and scattering coefficients) of the model. The inverse calculation reconstructs the distribution of the optical coefficient by using Newton′s method to minimize the difference between theory and measured data. Due to ill-posed nature of the inverse problem, Tikhonov regularization is utilized to stabilize the reconstruction result. For verification of developed reconstruction algorithm, different designated simulation cases, including different optical coefficients, size, and location of tumor, were used. The reconstruction results then were assessed by a set of resolution measures that compare reconstructed image with target one, and provide the quantitatively evaluation for the reconstructed image quality. Moreover, reconstruction images were also quantitatively evaluated by using mean square error (MSE). The evaluation results shows that, under condition of using 80-mm-diamater cylinder phantom, tumor with diameter more than 15 mm, located at the off-center distance 0 mm and contrast of 2, can be reconstructed. However, if the optical contrast of tumor were more than 2.5, it would lead to over-estimation of optical properties. It also shows significant crosstalk issue between absorption and scattering coefficients if the ratio of absorption-contrast to scattering-contrast is more than 1.5.
關鍵字(中) ★ 三維擴散光學斷層造影
★ 有限元素法
★ Tikhonov正則化
★ 腫瘤特徵辨識
★ 影像評估
關鍵字(英) ★ three-dimensional diffuse optical tomography
★ finite element method
★ Tikhonov regularization
★ identification of tumor
★ quantitative evaluation of image quality
論文目次 摘要 I
Abstract II
誌謝 III
目錄 IV
圖目錄 VI
表目錄 VIII
第一章 緒論 1
1-1 研究動機與目的 1
1-2 乳房組織光學特性 2
1-3 文獻回顧 5
1-4 論文架構 6
第二章 正向問題 7
2-1 有限元素法求解擴散方程式 8
第三章 逆向問題 12
3-1 建立逆向問題 12
3-2 雅可比(Jacobian)矩陣 13
3-3 雅可比(Jacobian)矩陣之正規化(normalization) 14
3-4 逆向問題之正則化(regularization) 15
第四章 模擬與驗證 16
4-1 模擬資料建立 16
4-2 影像重建 20
4-3 模擬驗證 21
4-3-1 幾何特徵辨識 22
4-3-2 光學特徵辨識 33
4-4 影像評估與分析 37
第五章 結論與未來展望 47
5-1 結論 47
5-2 未來展望 48
參考文獻 49
參考文獻 1 E. Vandeweyer, and D. Hertens, “Quantification of glands and fat in breast tissue: An experimental determination,” Ann. Anat., 184, 181–184, 2002.
2 B. B. Das, F. Liu, and R. R. Alfano, “Time-resolved fluorescence and photon migration studies in biomedical and model random media,” Rep. Prog. Phys., 60, 227-292, 1997.
3 G. Maskarinec, I. Pagano, G. Lurie, L. R. Wilkens, L. N. Kolonel, “Mammographic density and breast cancer risk: the Multiethnic Cohort Study,” Am. J. Epidemiol., 162, 743-752, 2005.
4 V. A. McCormack, I. dos Santos Silva, “Breast density and parenchymal patterns as markers of breast cancer risk: a Meta-analysis,” Cancer Epidemiol Biomarkers Prev., 15. 1159–1169, 2006.
5 M. Yaffe, “Review: Measurement of Mammographic Density,” Breast Cancer Res., 10, 209–219, 2008.
6 M. Varjonen, “Three-Dimensional digital breast tomosynthesis in the early diagnosis and detection of breast cancer,” in Digital Mammography, (Springer Berlin Heidelberg, 2006), pp. 152-159.
7 L. L. Humphrey, M. Helfand, B. K. Chan, and S. H. Woolf, “Breast cancer screening: a summary of the evidence for the U.S. Preventive Services Task Force,” Ann. Intern. Med., 137, 347-367, 2002.
8 S. G. Komen for the Cure, Types of Breast Cancer Tumors (Susan G. Komen for the Cure, 2008), pp. 806-369.
9 A.Rim and M. Chellman-Jeffers, “Trends in breast cancer screening and diagnosis,” Cleve. Clin. J. Med., 75, 2-9, 2008.
10 National Breast and Ovarian Cancer Centre, Breast cancer risk factors: a review of the evidence (National Breast and Ovarian Cancer Centre, 2009).
11 L. Wang, P. P. Ho, C. Liu, G. Zhang, and R. R. Alfano, “Ballistic 2-D Imaging Through Scattering Walls Using an Ultrafast Optical Kerr Gate,” Reports, 16, 769-771, 1991.
12 L. Wang, X. Liang, P. Galland, P. P. Ho, and R. R. Alfano, “True scattering coefficients of turbid matter measured by early-time gating,” Opt. Lett., 20, 913-915, 1995.
13 J. V. Garcia, F. Zhang and P. C. Ford, “Multi-photon excitation in uncaging the small molecule bioregulator nitric oxide,” Phil. Trans. R. Soc. A, 371, 20120129, 2013.
14 S. B Fox, D. G. Generali and A. L. Harris, “Review: Breast tumour angiogenesis,” Breast Cancer Res., 9, 216, 2007.
15 A. Cerussi, D. Hsiang, N. Shah, R. Mehta, A. Durkin, J. Butler, and B. J. Tromberg, “Predicting response to breast cancer neoadjuvant chemotherapy using diffuse optical spectroscopy,” PNAS, 104, 4014-4019, 2007.
16 S. R. Arridge, and J. C. Hebden, “Optical imaging in medicine: II. Modelling and reconstruction,” Phys. Med. Biol., 42, 841-853, 1997.
17 L. Y. Chen, M. C. Pan, M. C. Pan, “Flexible near-infrared diffuse optical tomography with varied weighting functions of edge-preserving regularization,” Appl. Opt., 52, 1173-1182, 2013.
18 M. Schweiger and S. R. Arridge, “Comparison of two- and three-dimensional reconstruction methods in optical tomography,” Appl. Opt., 37, 7419-7428, 1998.
19 H. Jiang, “Three-dimensional optical image reconstruction: finite element approach,” in Advances in Optical Imaging and Photon Migration, J. Fujimoto and M. Patterson, eds., Vol. 21 of OSA Trends in Optics and Photonics (Optical Society of America, 1998), paper ATuC3.
20 F. Gao, P. Poulet, and Y. Yamada, “Simultaneous mapping of absorption and scattering coefficients from a three-dimensional model of time-resolved optical tomography,” Appl. Opt., 39, 5898-5910, 2000.
21 B. W. Pogue, S. Geimer, T. O. McBride, S. Jiang, U. L. Österberg, and K. D. Paulsen, “Three-dimensional simulation of near-infrared diffusion in tissue: boundary condition and geometry analysis for finite-element image reconstruction,” Appl. Opt., 40, 588-600, 2001.
22 H. Jiang, Y. Xu, N. Iftimia, J. Eggert, K. Klove, L. Baron, and L. Fajardo, “Three-dimensional optical tomographic imaging of breast in a human subject,” IEEE Trans. Med. Imaging., 20, 1334–1340, 2001.
23 J. Culver, R. Choe, M. Holboke, L. Zubkov, T. Durduran, A. Slemp, V. Ntziachristos, D. Pattanayak, B. Chance, and A. Yodh, “3D diffuse optical tomography in the plane parallel transmission geometry: Evaluation of a hybrid frequency domain/continuous wave clinical system for breast imaging,” Med. Phys., 30, 235–247, 2003.
24 H. Dehghani, B. W. Pogue, S. P. Poplack, and K. D. Paulsen, “Multiwavelength three-dimensional near-infrared tomography of the breast: initial simulation, phantom, and clinical results,” App. Opt., 42, 135–145, 2003.
25 N. Iftimia, X. Gu, Y. Xu, H. Jiang, “A compact, parallel-detection diffuse optical mammography system,” Rev. Sci. Instr., 74, 2836–2842, 2003.
26 A. Li, E. L. Miller, M. E. Kilmer, T. J. Brukilacchio, T. Chaves, J. Stott, Q. Zhang, T. Wu, M. Chorlton, R. H. Moore, D. B. Kopans, and D. A. Boas, “Tomographic optical breast imaging guided by three-dimensional mammography,” Appl. Opt., 42, 5181–5190, 2003.
27 S. K. Biswas, K. Rajan and R. M. Vasu, “Practical Fully 3-D Reconstruction mography,” J. Opt. Soc. Am. A. Opt. Image. Sci. Vis., 29, 1017-1026, 2012.
28 K. D. Paulsen, and H. Jiang, “ Spatially varying optical property reconstruction using a finite element diffusion equation approximation,” Med. Phys., 22(6), 691-701, 1995.
29 S. R. Arridge, M. Schweiger, M. Hiraoka, and D. T. Delpy, “ A finite element approach for modeling photon transport in tissue, ” Med. Phys., 20(2) 299-309, 1993.
30 T. J. Farrell, M. S. Patterson, and B. C. Wilson, “A diffusion theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo, ” Med. Phys., 19(4), 879-888, 1992.
31 W. Egan, Optical properties of inhomogeneous materials: Applications to geology, astronomy chemistry, and engineering. (Elsevier, 2012).
32 K. D. Paulsen, and H. Jiang, “Spatially varying optical property reconstruction using a finite element diffusion equation approximation,” Med. Phys., 22(6), 691-701, 1995.
33 S. R. Arridge, M. Schweiger, M. Hiraoka, and D. T. Delpy, “A finite element approach for modeling photon transport in tissue,” Med. Phys., 20(2), 299-309, 1993.
34 J. C. Hebden, H. Veenstra, H. Dehghani, E. M. C. Hillman, M. Schweiger, S. R. Arridge, D. T. Delpy, “Three-dimensional time-resolved optical tomography of a conical breast phantom,” Appl. Opt., 40, 3278-3287, 2001.
35 Y. Xu, X. Gu, L. Fajardo, and H. Jiang, “In vivo breast imaging with diffuse optical tomography based on higher-order diffusion equations,” Appl. Opt., 42, 3163-3169, 2003.
36 S. Jiang, B. W. Pogue, S. Davis, and K. D. Paulsen, “Multispectral NIR Diffuse Optical Tomography System Development,” in Biomedical Optics, Technical Digest (CD) (Optical Society of America, 2006), paper SH35.
37 B. W. Pogue, S. P. Poplack, T. O. McBride, W. A. Wells, K. S. Osterman, U. L. Osterberg, and K. D. Paulsen, “Quantitative hemoglobin tomography with diffuse near-infrared spectroscopy: pilot results in the breast,” Radiology, 218, 261-266, 2001.
38 L. Chen, M. Pan, and M. Pan, “Implementation of edge-preserving regularization for frequency-domain diffuse optical tomography,” Appl. Opt. 51, 43-54, 2012.
39 M. Pan, C. Chen, L. Chen, M. Pan, Y. Shyr, “Highly resolved diffuse optical tomography: a systematic approach using high-pass filtering for value-preserved images.” J. Biomed. Opt., 13(2), 024022-024022-14, 2008.
指導教授 潘敏俊(Min-chun PAN) 審核日期 2016-2-26
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明