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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 陳志宏 | |
dc.contributor.author | Chia-Ming Chang | en |
dc.contributor.author | 張佳銘 | zh_TW |
dc.date.accessioned | 2021-06-15T06:44:10Z | - |
dc.date.available | 2016-08-22 | |
dc.date.copyright | 2011-08-22 | |
dc.date.issued | 2011 | |
dc.date.submitted | 2011-08-19 | |
dc.identifier.citation | [1]. Chun-Yuan Chang, “The Development of NTU Chinese Standard Brain Template: Morphologic Comparison and Application in Functional Magnetic Resonance Imaging.” Department of Electrical Engineering, National Taiwan University, Master Thesis; 2008.
[2]. J. Talairach and P. Tournoux. “Co-planar stereotactic atlas of the human brain: 3-Dimensional proportional system: an approach to cerebral imaging Stuttgart.” Georg Thieme Verlag, 1988. [3]. Matthew Brett, Ingrid S. Johnsrude and Adrian M. Owen. “The problem of functional localization in the human brain.” Neurosience; 2002; 3:243-249. [4]. Evans AC, Collins DL, Mills SR, Brown ED, Kelly RL, Peters TM. “3D statistical neuroanatomical models from 305 MRI volumes.” Proc IEEE Nucl Science Symp Medl Imaging Conf 1993: 1813-7. [5]. Ogawa, S., Lee, T.M., Nayak, A.S., and Glynn, P. “Oxygenation-sensitive contrast in magnetic resonance image of rodent brain at high magnetic fields.” Magn Reson Med 1990; 14, 68-78. [6]. D. Louis Collins, “3D Model-based segmentation of individual brain structures from magnetic resonance imaging data.” Department of Biomedical Engineering, McGill University, Montreal, PhD Thesis. [7]. John Ashburner and Karl J. Friston, “Nonlinear Spatial Normalization Using Basis Functions.” Functional Imaging Laboratory, Wellcome Department of Cognitive Neurology, Institute of Neurology, London, United Kingdom, Human Brain Mapping 7:254–266(1999). [8]. B.K.P. Horn and B.G. Schunck, “Determining optical flow.” Artificial Intelligence, vol 17, pp 185-203, 1981. [9]. P. Kochunov, “Localized morphological brain differences between English-speaking Caucasians and Chinese-speaking Asians: new evidence of anatomical plasticity.” Research Imaging Center, University of Texas Health Science Center at San Antonio, NEUROREPORT, 2003. [10]. The Statistical Parametric Mapping. http://www.fil.ion.ucl.ac.uk/spm/ [11]. FMRIB Software Library. http://www.fmrib.ox.ac.uk/fsl/ [12]. Zilles, K., Kawashima, R., Dabringhaus, A., Fukuda, H., & Schormann, T. (2001). Hemispheric shape of European and Japanese brains: 3-D MRI analysis of intersubject variability, ethnical, and gender differences. Neuroimage, 13, 262–271. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/47998 | - |
dc.description.abstract | 由於大腦的結構複雜,並且大腦神經功能會隨著不同的性別、年齡與人種產生改變,因此在神經認知科學研究上許多資料的分析,需要標準的大腦圖譜為基準。為了建立構造與功能的關連性,西方學者Talairach就訂立一套三度空間座標系統,搭配上大體解剖的腦切片互相對照,建立廣為人使用的圖譜。之後為了有群體代表性,Montreal Neurologic Institute (MNI)收集了305筆的大腦MRI影像。並藉由重新定位,線性變型等影像處理步驟,將此三百餘人的大腦影像進行平均並且在Talairach所訂立的三維座標系上建立了以群體為基礎的大腦圖譜MNI 305,此方法也為後世製作圖譜的準則。之後MNI又分別建立了ICBM_152與Collins_27標準圖譜,皆廣受世界所應用。
然而經由過去實驗發現[1],東西方人種在腦部的大小與形狀上有明顯的差異,若是在華人功能性磁振影的資料分析上直接套用由西洋人種大腦所建立的MNI圖譜,反應區域會較不符合解剖的構造;為了解決此問題,醫學影像實驗室收集了95筆大腦MRI影像,採用與MNI圖譜相似的處理程序,建立了Taiwan University Chinese Brain Template (NTU template)。但是目前NTU template仍缺乏神經功能的分區無法直接應用在華人功能性磁振影的資料分析上;為了解決此問題,我們建立了一套利用光流(Optical flow)估計影像形變的非線性對位演算法,將NTU template與ICBM_152模板影像進行非線性影像對位,並把ICBM_152所帶的神經功能分區信息映射至NTU template上。將本論文的對位方式與目前常被使用的神經認知分析軟體所帶的對位功能進行比較,發現本論文所採用的方式能得到更佳的對位結果。 應用NTU template於華人的神經認知功能性影像實驗分析上,能得到更合理的判讀結果。並且藉由比較NTU template與ICBM_152的功能區分佈比例,發現東西方人腦功能區的分佈存在差異,而此差異主要是由結構上非線性形變所造成的。未來我們將以非線性對位的方式建立一組更高解析度的圖譜,希望在大腦功能定位、神經科學研究及臨床醫學應用上有所助益。 | zh_TW |
dc.description.abstract | Most data analyses were developed based on the standard brain template in the field of neuroimaging research, because of the complexity and variability of human brain. For figuring out the relationship between brain function and structure, Talairach set a three-dimensional coordinate system, cooperating with the postmortem brain autopsy, and thus a worldwide adopted standard brain atlas was created.
For the purpose of anatomic representation of general population, Montreal Neurologic Institute (MNI) collected 305 brains MRI image, and adopted image processing methods such as realignment and transformation to create a population-based standard brain template by averaging three hundreds brain dataset and this process became standard method for building template. The MNI also created ICBM_152 and colin27 which both are worldwide adopted nowadays. However the difference of brain structures between western and eastern people was observed in past experiment [1]. The mismatch issue may lead to bias or inappropriate interpretation in neurocognitive studies. In this thesis, NTU Medical Image Lab recruited ninety-five subjects and developed the National Taiwan University standard brain template (NTU template)[1] based on the process of MNI template. But NTU template lacked of functional area information, which can’t be used on fMRI study directly. To solve this problem, we established an optical flow nonlinear registration algorithm, spatial normalizing ICBM_152 to NTU template and mapped ICBM_152’s functional area information to NTU template. Compared with other fMRI software’s registration function, we found that the method we used can provide better registration result. Using NTU template in fMRI data analyses can get more precise localization in fMRI experiments. After compared functional area distribution between NTU template and ICBM_152, we found that distribution exist different between eastern and western,which caused by structure’s nonlinear deformation. In the future, we will work on higher resolution template, which may benefit in neuroscience study, human brain mapping and clinical applications. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T06:44:10Z (GMT). No. of bitstreams: 1 ntu-100-R98945009-1.pdf: 2785925 bytes, checksum: 780a1a4e936224d379f5d6bc711f773e (MD5) Previous issue date: 2011 | en |
dc.description.tableofcontents | 致謝 I
摘要 II ABSTRACT IV 目錄 VI 表目錄 VIII 圖目錄 IX 第一章 緒論 1 1.1前言 1 1.2研究背景 1 1.2.1 Talairach座標系統 1 1.2.2 Talairach腦部圖譜 2 1.2.3 蒙特羅神經協會腦部模板 4 1.2.4標準華人腦部圖譜 6 1.3 研究動機 8 1.4 研究目的 9 第二章 文獻回顧 10 2.1影像對位 10 2.2座標轉換 11 2.2.1線性座標轉換 12 2.2.1.1三維仿射座標轉換 (Affine transformation) 12 2.2.2非線性座標轉換: 16 2.2.2.1多項式座標轉換: 16 2.2.2.2自由形變 17 2.2.2.3使用基本函數控制形變: 17 2.3尺度空間(Scale space) 19 2.4影像特徵偵測 21 2.5相似函數與目標函數: 24 2.6參數優化: 24 2.6.1階級式優化: 25 第三章 NTU template功能區自動標定 26 3.1實驗流程 26 3.2影像對位 27 3.2.1線性對位 27 3.2.2非線性對位 28 3.2.2.1光流(Optical flow) 29 3.2.2.2 Horn–Schunck method 30 3.2.2.3光流對位 33 3.3對位結果 34 3.4 對位結果驗證 36 第四章 NTU template區域資訊的應用 38 4.1 區域資訊的映射 38 4.2 NTU Template區域資訊標定結果 38 4.3應用於東西方人功能區域差異比較 39 4.3.1比較方式 39 4.3.2比較結果 40 4.4應用於功能性影像實驗 42 4.4.1 Block Design與Event Related 42 4.4.2資料分析 42 4.4.3 Motor homunculus 43 4.4.4 FMRI實驗 44 4.4.5實驗設計與資料分析 44 4.4.6實驗結果 44 第五章 討論 53 5.1不同對位方式的比較 53 5.1.1比較方式 53 5.1.2量化比較結果 56 5.2 NTU template 與 ICBM_152 的比較 58 5.2.1量化比較 59 5.3 腦葉差異與結構上的關係 61 第六章 結論與未來工作 62 6.1結論 62 6.2未來工作 62 參考文獻 64 附錄一:三維影像處理運算子 66 A1.1三維索貝爾算子(Sobel operator) 66 A1.2三維拉譜拉斯-高斯運算子 67 附錄二:功能性磁振造影 68 | |
dc.language.iso | zh-TW | |
dc.title | 華人大腦標準模板神經功能區的自動標定 | zh_TW |
dc.title | Model-Based Automatic Functional Area Labeling for NTU Standard Brain Template | en |
dc.type | Thesis | |
dc.date.schoolyear | 99-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 廖漢文,陳中明,林慶波,莊永裕,梁庚辰 | |
dc.subject.keyword | 華人大腦圖譜,MNI圖譜,圖譜,影像對位,功能性磁振造影, | zh_TW |
dc.subject.keyword | NTU template,MNI template,atlas,Image registration,Functional magnetic resonance imaging (fMRI), | en |
dc.relation.page | 69 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2011-08-20 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 生醫電子與資訊學研究所 | zh_TW |
顯示於系所單位: | 生醫電子與資訊學研究所 |
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