Using Coherence Index to Determine the Optimum Diffusion Tensor Encoding Steps for White Matter Tractography
碩士 === 國立臺灣大學 === 醫學工程學研究所 === 93 === Recently, the technique of Diffusion Magnetic Resonance Imaging (Diffusion MRI) has developed to make progress in explaining perpetual controversy about neuroscience in human brain. Diffusion Tensor magnetic resonance Imaging (DTI) has been recognized as an impo...
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ndltd-TW-093NTU055300092015-12-21T04:04:53Z http://ndltd.ncl.edu.tw/handle/33783017358773156945 Using Coherence Index to Determine the Optimum Diffusion Tensor Encoding Steps for White Matter Tractography 利用相似度決定白質神經纖維束成像之最佳擴散張量梯度數目 Shiou-Ping Lee 李秀萍 碩士 國立臺灣大學 醫學工程學研究所 93 Recently, the technique of Diffusion Magnetic Resonance Imaging (Diffusion MRI) has developed to make progress in explaining perpetual controversy about neuroscience in human brain. Diffusion Tensor magnetic resonance Imaging (DTI) has been recognized as an important tool to reveal the axonal fiber tracts in cerebral white matter noninvasively in the clinical diagnosis image. By probing the translational displacement of water molecules, it provides the primary direction of water molecular diffusion which is correlated to the main pathway of fiber bundles. The eigenvector of the diffusion tensor at each location in the cerebral white matter represents the fiber orientation at the same location. Based on this information, 3D reconstruction and visualization of white matter fiber pathways can be produced by tractography. The last, MR-DTI has achieved a reasonable cognition and judgement, making a difference from the past acquisition strategies for complicated structure of white matter bundles. International eminent functional brain science research center has investigated related lectures for tractography algorithm and available tools, and we also proposed a novel fiber tracking algorithm. It extracted salient tensor feature using a local regularization theory that represented SDWI method. By using a phantom image made up of PE fibers with known fiber pathways to validate stability of this algorithm. Extensive attention and profound analysis has been given to recover identifiable anatomical structures that correspond to fiber tracjectories, and the position of brain lesions in vast Tractography innovation has played more important role. We has derived from Tractography quantitative index a formula that determines the correlation between optimum diffusion tensor encoding steps and white matter tractography. Its dominant strategy has not been proven by the traditional Tractography research and related application in the clinical experiment parameter. Chung-Ming Chen 陳中明 2005 學位論文 ; thesis 46 zh-TW |
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碩士 === 國立臺灣大學 === 醫學工程學研究所 === 93 === Recently, the technique of Diffusion Magnetic Resonance Imaging (Diffusion MRI) has developed to make progress in explaining perpetual controversy about neuroscience in human brain. Diffusion Tensor magnetic resonance Imaging (DTI) has been recognized as an important tool to reveal the axonal fiber tracts in cerebral white matter noninvasively in the clinical diagnosis image. By probing the translational displacement of water molecules, it provides the primary direction of water molecular diffusion which is correlated to the main pathway of fiber bundles. The eigenvector of the diffusion tensor at each location in the cerebral white matter represents the fiber orientation at the same location. Based on this information, 3D reconstruction and visualization of white matter fiber pathways can be produced by tractography.
The last, MR-DTI has achieved a reasonable cognition and judgement, making a difference from the past acquisition strategies for complicated structure of white matter bundles. International eminent functional brain science research center has investigated related lectures for tractography algorithm and available tools, and we also proposed a novel fiber tracking algorithm. It extracted salient tensor feature using a local regularization theory that represented SDWI method. By using a phantom image made up of PE fibers with known fiber pathways to validate stability of this algorithm.
Extensive attention and profound analysis has been given to recover identifiable anatomical structures that correspond to fiber tracjectories, and the position of brain lesions in vast Tractography innovation has played more important role. We has derived from Tractography quantitative index a formula that determines the correlation between optimum diffusion tensor encoding steps and white matter tractography. Its dominant strategy has not been proven by the traditional Tractography research and related application in the clinical experiment parameter.
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author2 |
Chung-Ming Chen |
author_facet |
Chung-Ming Chen Shiou-Ping Lee 李秀萍 |
author |
Shiou-Ping Lee 李秀萍 |
spellingShingle |
Shiou-Ping Lee 李秀萍 Using Coherence Index to Determine the Optimum Diffusion Tensor Encoding Steps for White Matter Tractography |
author_sort |
Shiou-Ping Lee |
title |
Using Coherence Index to Determine the Optimum Diffusion Tensor Encoding Steps for White Matter Tractography |
title_short |
Using Coherence Index to Determine the Optimum Diffusion Tensor Encoding Steps for White Matter Tractography |
title_full |
Using Coherence Index to Determine the Optimum Diffusion Tensor Encoding Steps for White Matter Tractography |
title_fullStr |
Using Coherence Index to Determine the Optimum Diffusion Tensor Encoding Steps for White Matter Tractography |
title_full_unstemmed |
Using Coherence Index to Determine the Optimum Diffusion Tensor Encoding Steps for White Matter Tractography |
title_sort |
using coherence index to determine the optimum diffusion tensor encoding steps for white matter tractography |
publishDate |
2005 |
url |
http://ndltd.ncl.edu.tw/handle/33783017358773156945 |
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