{"title":"扩散张量成像(DTI)中的可视化技术分析","authors":"Anzer M Muhammed, A. V., E. K","doi":"10.1109/ICAECC.2018.8479448","DOIUrl":null,"url":null,"abstract":"Human brain is the command centre of the human body. It receives input from sensory organs and sends outputs to the muscles. Brain consists of two types of tissue mainly white matter tissue (anisotropic) and grey matter tissue (isotropic). Active examining of the brain functioning requires certain brain imaging techniques. In order to solve this problem Magnetic resonance imaging (MRI) technique was implemented for the imaging of grey matter of the brain. In 1994 Peter Baser introduced Diffusion Tensor Imaging (DTI), DTI is an advanced variant of MRI which is being implemented for the imaging of white matter tissue of the brain. It uses present MRI technology and no other equipment is required. DTI technique undergoes visualization of the random motion of the water molecules in the white matter tissue of the brain. The random motion of the water molecules can determine the anisotropic and isotropic nature of the white matter portion of the brain. The parameter of analysing the isotropic and anisotropic range is the Fractional Anisotropy (FA). Here, three visualization techniques for DTI namely Scalar Indices, Tensor Glyph, and Fibre Tractography are studied and analysed. The analysis focuses on extracting useful information of the brain in different aspects. This can be useful in studying the internal patterns of the brain which will help in medical diagnosis.","PeriodicalId":106991,"journal":{"name":"2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Analysis of Visualization Techniques in Diffusion Tensor Imaging (DTI)\",\"authors\":\"Anzer M Muhammed, A. V., E. K\",\"doi\":\"10.1109/ICAECC.2018.8479448\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Human brain is the command centre of the human body. It receives input from sensory organs and sends outputs to the muscles. Brain consists of two types of tissue mainly white matter tissue (anisotropic) and grey matter tissue (isotropic). Active examining of the brain functioning requires certain brain imaging techniques. In order to solve this problem Magnetic resonance imaging (MRI) technique was implemented for the imaging of grey matter of the brain. In 1994 Peter Baser introduced Diffusion Tensor Imaging (DTI), DTI is an advanced variant of MRI which is being implemented for the imaging of white matter tissue of the brain. It uses present MRI technology and no other equipment is required. DTI technique undergoes visualization of the random motion of the water molecules in the white matter tissue of the brain. The random motion of the water molecules can determine the anisotropic and isotropic nature of the white matter portion of the brain. The parameter of analysing the isotropic and anisotropic range is the Fractional Anisotropy (FA). Here, three visualization techniques for DTI namely Scalar Indices, Tensor Glyph, and Fibre Tractography are studied and analysed. The analysis focuses on extracting useful information of the brain in different aspects. This can be useful in studying the internal patterns of the brain which will help in medical diagnosis.\",\"PeriodicalId\":106991,\"journal\":{\"name\":\"2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAECC.2018.8479448\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAECC.2018.8479448","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of Visualization Techniques in Diffusion Tensor Imaging (DTI)
Human brain is the command centre of the human body. It receives input from sensory organs and sends outputs to the muscles. Brain consists of two types of tissue mainly white matter tissue (anisotropic) and grey matter tissue (isotropic). Active examining of the brain functioning requires certain brain imaging techniques. In order to solve this problem Magnetic resonance imaging (MRI) technique was implemented for the imaging of grey matter of the brain. In 1994 Peter Baser introduced Diffusion Tensor Imaging (DTI), DTI is an advanced variant of MRI which is being implemented for the imaging of white matter tissue of the brain. It uses present MRI technology and no other equipment is required. DTI technique undergoes visualization of the random motion of the water molecules in the white matter tissue of the brain. The random motion of the water molecules can determine the anisotropic and isotropic nature of the white matter portion of the brain. The parameter of analysing the isotropic and anisotropic range is the Fractional Anisotropy (FA). Here, three visualization techniques for DTI namely Scalar Indices, Tensor Glyph, and Fibre Tractography are studied and analysed. The analysis focuses on extracting useful information of the brain in different aspects. This can be useful in studying the internal patterns of the brain which will help in medical diagnosis.