跳到主要內容

臺灣博碩士論文加值系統

(44.192.22.242) 您好!臺灣時間:2021/07/31 10:28
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:陳玉芬
研究生(外文):Yu-Fen Chen
論文名稱:利用局部調適閾值技術找出腦血流灌注影像中腦脊髓液位置
論文名稱(外文):Through the local adaptive thresholding techniques to identify CSF pixels on brain perfusion MRI
指導教授:高怡宣高怡宣引用關係
指導教授(外文):Yi-Hsuan Kao
學位類別:碩士
校院名稱:國立陽明大學
系所名稱:生物醫學影像暨放射科學系暨研究所
學門:醫藥衛生學門
學類:醫學技術及檢驗學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:中文
論文頁數:71
中文關鍵詞:腦脊髓液磁場不均勻性局部調適閾值技術腦血流灌注磁振影像
外文關鍵詞:cerebrospinal fluidfield inhomogeneitylocal adaptive thresholdingbrain perfusion MRI
相關次數:
  • 被引用被引用:0
  • 點閱點閱:204
  • 評分評分:
  • 下載下載:20
  • 收藏至我的研究室書目清單書目收藏:0
目的:在腦部血流灌注磁振影像技術,會使用參數影像來判斷病灶區,但是腦脊髓液和病灶區域的平均穿流時間和峰值時間等參數影像訊號相似,造成診斷上測量病灶面積大小的困難。因此本論文目的在於利用局部調適閾值技術,找出腦脊髓液位置,並將其移除,以輔助診斷。
材料與方法:在血流灌注動態磁振影像中,第一張影像尚未受到射頻脈衝飽和,腦脊髓液訊號強度遠較之後受到飽和的影像大,而腦實質的訊號強度並沒有太大差異。因此可以利用兩張影像訊號變化的特性,分割腦脊髓液及腦實質組織。本實驗以電腦模擬影像作為影像分割評估標準,在計算模擬影像時,考慮雜訊及接收線圈所造成的磁場不均勻性,以符合臨床實際影像的訊號強度分布。在進行影像分割之前,先修正影像之磁場不均勻性問題,再分別使用Otsu’s演算法和局部調適閾值方法,找出腦脊髓液位置,且評估其正確性。
結果:由於磁場造成訊號不均勻的關係,僅以未進行修正的第一張影像配合影像分割技術的遮罩結果較差。利用影像相除技術可消除不均勻性問題;使用Otsu’s演算法和局部調適閾值方法皆有效地找出位於腦室位置的腦脊髓液成分,但對於大腦邊緣含腦脊髓液量較少的位置而言,以局部調適閾值方法進行影像分割結果較好。
結論:我們所提出的局部調適閾值影像分割技術搭配影像相除修正磁場不均勻性,可以有效的分割出腦脊髓液成份,不需要額外的造影和影像處理步驟,即可正確且快速地測量出病灶區域在血流灌注參數影像中的面積大小。
Purpose: In MR brain perfusion studies, we often use the parametric images to confirm the location of lesion. Due to the abnormal hyperintensity of cerebral spinal fluid (CSF) in mean transit time (MTT) and time to peak (TTP) maps, there are ambiguities in measuring the lesion size. The purpose of this study is removing the CSF pixels on perfusion parametric images by using local adaptive thresholding techniques to improve the clinical diagnosis.
Material and methods: In dynamic susceptibility contrast MR imaging, the longitudinal magnetization is not saturated by radio-frequency pulse on the first image, so the signal intensity of CSF is higher than that on the later images, which had been saturated. We can classify the CSF and brain parenchyma by using the signal intensity difference between the two images. Since the field inhomogeneity is unfavorable for image segmentation, we have to start with correcting the inhomogeneity, then using the global and local threshold methods to find the CSF pixels.
Results: By using image division to eliminate the inhomogeneous field, the CSF pixels can be effectively removed. CSF at the ventricle could be found accurately in all the thresholding methods. The local adaptive thresholding techniques is more suitable to segment the cortical CSF.
Conclusions: We developed the local adaptive thresholding with image division to determine the CSF pixels. It is a proper method to identify the location and area of the lesion in clinical diagnosis.
摘要 3
ABSTRACT 4
1 緒論 5
1.1 研究背景 5
1.2 論文架構 7
2 材料與方法 8
2.1 分析材料 8
2.1.1 臨床影像 8
2.1.2 電腦模擬影像 9
2.2 射頻磁場不均勻性修正-影像相除 12
2.3 影像分割技術 16
2.3.1 影像二值化 16
2.3.2 Otsu’s method 17
2.3.3 Niblack’s method 19
2.3.4 Sauvola’s method 20
2.3.5 Feng’s method 21
2.4 遮罩效果評估方法 23
2.5 實驗設備 26
2.6 實驗流程 27
3 實驗結果 28
3.1 模擬影像 28
3.1.1 第一張影像進行閾值計算 29
3.1.2 影像相除後進行閾值計算 31
3.1.3 遮罩效果比較 34
3.2 臨床影像 39
3.2.1 第一張影像進行閾值計算 40
3.2.2 影像相除後進行閾值計算 43
3.3 使用腦脊髓液遮罩於臨床腦部血流灌注參數影像 46
3.3.1 腦血流灌注功能正常受試者 46
3.3.2 頸動脈狹窄病人 49
3.3.3 腦梗塞病人 55
4 討論 61
4.1 遮罩效果比較 61
4.1.1 電腦模擬影像 61
4.1.2 臨床影像 63
4.2 磁場不均勻性修正是否必要 65
4.3 遮罩結果是否受到血管位置影響 66
5 結論 67
參考文獻 68
Collins, D. L., Zijdenbos, A. P., Kollokian, V., Sled, J. G., Kabani, N. J., Holmes, C. J., Evans, A. C. (1998). Design and construction of a realistic digital brain phantom. IEEE Transactions on Medical Imaging, 17(3), 463-468.
Fawcett, T. (2004). ROC graphs: notes and practical considerations for researchers. Technical Report HPL-2003-4, Hewlett Packard Labs.
Feng, M. L. & Tang, Y. P. (2004). Contrast adaptive binarization of low quality document images. IEICE Electronics Express, 1(16), 501-506.
Fisher, M. & Albers, G. W. (1999). Applications of diffusion-perfusion magnetic resonance imaging in acute ischemic stroke. Neurology, 52, 1751-1756.
Haacke, E. M., Brown, R. W., Thompson, M. R., Venkatesan, R. (1999). Magnetic resonance imaging: Physical principles and sequence design. New York: John Wiley & Sons. (ISBN: 0471351288)
Ji, Q., Glass, J. O., Reddick, W. E. (2007). A novel, fast entropy-minimization algorithm for bias field correction in MR images. Magnetic Resonance Imaging, 25, 259-264.
Liang, Z. P. & Lauterbur P. C. (2000). Principles of magnetic: a signal processing perspective. New York, NY: IEEE Press.(ISBN: 0780347234)
Mihara, H., Iriguchi, N., Ueno, S.(1998). A method of RF inhomogeneity correction in MR imaging. Magnetic Resonance Material in Physics, Biology and Medicine, 7, 115-120.
Niblack, W(1986). An introduction to digital image processing. Prentice-Hall, Englewood Cliffs, NJ, 115-116.
Otsu, N. (1979). Threshold selection method from gray-level histogram. IEEE Transactions on Systems Man and Cybernetics, 9, 62-66.
Sauvola, J., Pietikäinen, M. (2000). Adaptive document image binarization. Pattern Recognition, 33, 225-236.
Sorensen, A. G., Buonanno, F. S., Gonzalez, R. G., Schwamm, L. H., Lev, M. H., Huang-Hellinger, F. R., Reese, T. G., Weisskoff, R. M., Davis, T. L., Suwanwela, N., Can, U., Moreira, J. A., Copen, W. A., Look, R. B., Finklestein, S. P., Rosen, B. R., Koroshetz, W. J. (1996). Hyperacute stroke: evaluation with combined multisection diffusion-weighted and hemodynamically weighted echo-planar MR imaging. Radiology, 199,391-401.
Suri, Jasjit S., Wilson, David L., Laxminarayan, Swamy (2005). Handbook of biomedical image analysis, v.2. segmentation models, part B. New York: Kluwer Academic/ Plenum Publishers. (ISBN: 0306486059)
Takahashi, M., Uematsu, H., Hatabu, H. (2003). MR imaging at high magnetic fields. Eur J Radiol, 46, 45-52.
Trier, Ø. D. & Jain, A. K. (1995). Goal-directed evaluation of binarization methods. IEEE Transactions on Pattern Analysis and Machine Intelligence, 17(12), 1191-1200.
Verrees, M. & Selman, W. R. (2004). Management of normal pressure hydrocephalus. American Family Physician, 70, 1071-1078.
Wirestam, R., Andersson, L., Ostergaard, L., Bolling, M., Aunola, J. P., Lindgren, A., Geijer, B., Holtas, S., Stahlberg, F. (2000). Assessment of regional cerebral blood flow by dynamic susceptibility contrast MRI using different deconvolution techniques. Magnetic Resonance in Medicine, 43, 691-700.
Yamada, K., Wu, O., Gonzalez, R. G., Bakker, D., Østergaard L., Copen, W. A., Weisskoff, R. M., Rosen, B. R., Yagi, K., Nishimura, T., Sorensen, A. G. (2002). Magnetic resonance perfusion- weighted imaging of acute cerebral infarction effect of the calculation methods and underlying vasculopathy. Stroke, 33, 87-94.
盧冠安(2008)。淺談生物分布預測模式。 自然保育季刊,第六十一期,3-6。
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top