By Susumu Mori, J-Donald Tournier
The recommendations at the back of diffusion tensor imaging (DTI) are generally tough to understand, even for magnetic resonance physicists. To make concerns worse, a many extra complicated higher-order equipment were proposed over the past few years to beat the now famous deficiencies of DTI. In Introduction to Diffusion Tensor Imaging: and better Order Models, those techniques are defined via wide use of illustrations instead of equations to assist readers achieve a extra intuitive knowing of the internal workings of those ideas. Emphasis is put on the translation of DTI photos and tractography effects, the layout of experiments, and the categories of software experiences that may be undertaken. Diffusion MRI is a truly lively box of study, and theories and methods are continuously evolving. To make feel of this regularly transferring panorama, there's a desire for a textbook that explains the ideas in the back of how those concepts paintings in a fashion that's effortless and intuitive to understand―Introduction to Diffusion Tensor Imaging fills this gap.
- Extensive use of illustrations to give an explanation for the suggestions of diffusion tensor imaging and comparable methods
- Easy to appreciate, even and not using a history in physics
- Includes sections on picture interpretation, experimental layout, and applications
- Up-to-date details on more moderen higher-order types, that are more and more getting used for scientific applications
Read or Download Introduction to Diffusion Tensor Imaging. And Higher Order Models PDF
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Additional resources for Introduction to Diffusion Tensor Imaging. And Higher Order Models
SENSE: sensitivity encoding for fast MRI. Magn Reson Med 1999;42:952À62. Skare S, Hedehus M, Moseley ME, Li TQ. Condition number as a measure of noise performance of diffusion tensor data acquisition schemes with MRI. J Magn Reson 2000;147:340À52. Zhou, X, Reynolds, HG. Quantitative analysis of eddy current effects on diffusion-weighted EPI. In Proceedings of the International Society for Magnetic Resonance in Medicine, Vancouver, Canada 1997; p. 1722. 1 TWO SCALAR MAPS (ANISOTROPY AND DIFFUSION CONSTANT MAPS) AND FIBER ORIENTATION MAPS ARE IMPORTANT OUTCOMES OBTAINED FROM DTI anisotropy The easiest way is to take the ratio of the longest and shortest axes (λ1/λ3).
For the same reason, it is not recommended to carry out signal averaging “on-the-fly” by the scanner. Instead, repeated measurements should be made and inspected individually; once corrupted images are averaged with noncorrupted ones, it becomes more difficult to determine the source of the ghosting effect. The disadvantages of this visual inspection approach are that it is time consuming, and the detection of ghosting artefacts relies on subjective judgment. An automated approach for ghost detection would be desirable for future research.
2 WE CAN OBTAIN THE SIX PARAMETERS FROM SEVEN DIFFUSION MEASUREMENTS In order to measure six diffusion constants along six independent axes, at least seven diffusion-weighted images are needed. This is because at least two data points are needed to obtain a diffusion constant from a slope of signal attenuation. We commonly obtain a least-diffusion-weighted image, the intensity of which corresponds to S0 in Eq. 2 (often called a b0 image, meaning b 5 0). Then, by obtaining another diffusionweighted image using, for example, the x-gradient (Sx), we can calculate an apparent diffusion constant along the x-axis (ADCx).