Generating Simulated DT-MRI Dataset

Generating Simulated DT-MRI Dataset

Dilek Goksel Duru, Mehmed Ozkan
Copyright: © 2008 |Pages: 8
DOI: 10.4018/978-1-59904-889-5.ch079
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Diffusion tensor magnetic resonance imaging (DTMRI), also known as diffusion tensor imaging (DTI), needs post processing by adequate image analysis and visualization tools. White matter tractography using DTI is becoming a routine MR technique to study white matter properties, connectivity, and alterations of fiber integrity due to pathology. The success of the method depends on the accuracy of the tracking algorithms. The disadvantage on the evaluation of such methods is that there is no gold standard regarding the true geometry of the brain anatomy or fiber bundles reconstructed in each particular case.

Key Terms in this Chapter

Gram-Schmidt Orthogonalization: A procedure which takes a nonorthogonal set of linearly independent vectors and constructs an orthogonal vector basis.

Stejskal Tanner Imaging Sequence: Spin-echo MRI imaging sequence with the addition of two diffusion-encoding gradients right before and after the 180o RF pulse.

Fiber Tractography: The process of using DTI data to estimate white matter structures.

Diffusion Coefficients: Characteristic parameters of the diffusion process such as apparent diffusion coeffient, fractional and relative anisotropy, linear, planar, and spherical anisotropy.

Anisotropic Diffusion: Any restriction in the Brownian movements of the free water protons due to physiological obstacles or any other anatomical barriers in a tissue.

Brownian Motion: The random movement of particles suspended in a fluid and the mathematical model used to describe such random movements.

Principal Diffusivity: The dominant diffusion direction determined by the largest eigenvector of the diffusion tensor.

Spin Echo (SE) Imaging Sequence: MRI imaging pulse sequence generated by applying 90o and 180o pulses for dephasing and rephasing the spins before the readout.

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