INTRODUCTION TO DIFFUSION TENSOR IMAGING SUSUMU MORI PDF
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Other factors can confound tractography. FA is basically a normalized variance of the eigenvalues:.
The streamline tract-tracing approach works by successively stepping in the direction of the principal eigenvector the direction of fastest diffusion. Visualization of second order tensor fields and matrix data. The trace is clinically useful in early stroke detection because it is sensitive to the initial cellular swelling cytotoxic edema which restricts diffusion [ 41 ].
The parallel diffusivity measure, also called the axial diffusivity, is equal to the largest eigenvalue. Clinical evaluation and follow-up outcome of diffusion tensor imaging-based functional neuronavigation: In the normal human brain, the trace is high in cerebrospinal fluid, around 9.
DTI is usually displayed by either condensing the information contained in the tensor into one number a scalaror into 4 numbers to give an R,G,B color and a brightness value.
Introduction to Diffusion Tensor Imaging – Susumu Mori – Google Books
The direction is different for each image, resulting in a different pattern of signal loss dark areas due to anisotropic diffusion.
Journal of molecular neuroscience. The color scheme most commonly used to represent the orientation of the major eigenvector works as follows: The introduction of the diffusion tensor model allowed, for the first time, a rotationally invariant description of the shape of water diffusion. Common false positive connections include trajectories from the corona radiata that cross the corpus callosum and trajectories from the corona radiata that cross at the pons and ascend in the corona radiata of the other hemisphere.
Journal of Magnetic Resonance Imaging. Another type of multiple b-value acquisition is diffusion spectrum imaging DSI [ 89 ]. Predicting human resting-state functional connectivity from structural connectivity. Wherever possible, pointers will be provided to more in-depth technical articles or books for further reading.
Weickert Joachim, Hagen Hans. The diffusion tensor was originally proposed for use in magnetic resonance imaging MRI by Peter Basser in [ 56 ]. Higher rank tensor models have been proposed to extend DTI [ 93 ]. For reviews of tractography techniques including explanations of common tractography artifacts and a comparison of methods see [ 5051 ]. The most common approach is streamline tractography Figure 6 [ 52535455 ], which is closely related to an earlier method for visualization of tensor fields known as hyperstreamlines [ 56 ].
The particular errors depend strongly on the tractography algorithm employed, and on the type of diffusion data used DTI versus higher-order models. Resolving crossings in the corticospinal tract by two-tensor streamline tractography: A brief history of DTI and its impact on clinical research The diffusion tensor was originally proposed for use in magnetic resonance imaging MRI by Peter Basser in [ 56 ].
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Finally, DTI is often viewed by estimating the course of white matter tracts through the brain via a process called tractography.
By repeating this process of diffusion weighting in multiple directions, a three-dimensional diffusion model the tensor can be estimated.
The diffusion tensor can also be viewed using glyphs, which are small 3D representations of the major eigenvector or whole tensor.
From single-pulsed field gradient to double-pulsed field gradient MR: These measures are useful for describing the amount of tissue organization and for locating voxels likely to contain a single white matter tract without crossing or fanning.
Another popular method is called FACT [ 54 ]. For the original paper that measured and compared several scalar measures, as well as the eigenvalues, in different regions of the human brain see [ 11 ]. Multi-shell acquisitions enable description of the full diffusion function using measures such as displacement, zero-probability and kurtosis that are highly sensitive to intrroduction [ 8788 ].
Inferring microstructural features and the physiological state of tissues from diffusion-weighted images. An example using glyphs and colors for DTI visualization. Example false negative streamline tractography error. MR diffusion kurtosis imaging imagkng neural tissue characterization. Applications to functional MRIch.
Example whole-brain streamline DTI tractography. Contributor Information Lauren J. Corresponding author Lauren J.
Illustration of anisotropic diffusion, in the ideal case of a coherently oriented tissue. Diffusion spectrum magnetic resonance imaging DSI tractography of crossing fibers.
In a study of neurosurgical patients with gliomas involving the motor tract, where patients were randomly assigned to study or control groups, DTI was shown to increase survival and reduce postoperative motor deficits [ 33 ].