https://scholars.lib.ntu.edu.tw/handle/123456789/365159
標題: | Principles and limitations of computational algorithms in clinical diffusion tensor MR tractography | 作者: | Chou, M.-C. Chen, C.-Y. HSIAO-WEN CHUNG |
公開日期: | 2011 | 卷: | 32 | 期: | 1 | 起(迄)頁: | 3-13 | 來源出版物: | American Journal of Neuroradiology | 摘要: | There have been numerous reports documenting the graphic reconstruction of 3D white matter architecture in the human brain by means of diffusion tensor MR tractography. Different from other reviews addressing the physics and clinical applications of DTI, this article reviews the computational principles of tractography algorithms appearing in the literature. The simplest voxel-based method and 2 widely used subvoxel approaches are illustrated first, together with brief notes on parameter selection and the restrictions arising from the distinct attributes of tract estimations. Subsequently, some advanced techniques attempting to offer improvement in various aspects are briefly introduced, including the increasingly popular research tracking tool using HARDI. The article explains the inherent technical limitations in most of the algorithms reported to date and concludes by providing a reference guideline for formulating routine applications of this important tool to clinical neuroradiology in an objective and reproducible manner. Copyright ? 2011 by the American Society of Neuroradiology. |
URI: | http://www.scopus.com/inward/record.url?eid=2-s2.0-78651482915&partnerID=MN8TOARS http://scholars.lib.ntu.edu.tw/handle/123456789/365159 |
DOI: | 10.3174/ajnr.A2041 | SDG/關鍵字: | algorithm; clinical practice; diffusion tensor imaging; false negative result; false positive result; human; image analysis; image quality; mathematical computing; motor activity; neuroimaging; neuroradiology; nonhuman; pyramidal tract; review; signal noise ratio; white matter; Algorithms; Brain; Brain Diseases; Diffusion Tensor Imaging; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Nerve Fibers, Myelinated; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity |
顯示於: | 生醫電子與資訊學研究所 |
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