Introduction to diffusion tensor imaging /
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| Author / Creator: | Mori, S. (Susumu) |
|---|---|
| Edition: | 1st ed. |
| Imprint: | Amsterdam ; Boston : Elsevier, 2007. |
| Description: | xiii, 176 p. : ill. (chiefly ill.) ; 31 cm. |
| Language: | English |
| Subject: | |
| Format: | Print Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/6686401 |
Table of Contents:
- Preface
- Chapter 1. Basics of diffusion measurement
- 1.1. NMR spectroscopy and MRI can detect signals from water molecules
- 1.2. What is diffusion?
- 1.3. How to measure diffusion?
- Chapter 2. Anatomy of diffusion measurement
- 2.1. A set of unipolar gradients and spin-echo sequence is most widely used for diffusion weighting
- 2.2. There are four parameters that affect the amount of signal loss
- 2.3. There are several ways of achieving a different degree of diffusion weighting
- Chapter 3. Mathematics of diffusion measurement
- 3.1. We need to calculate distribution of signal phases by molecular motion
- 3.2. Simple exponential decay describes signal loss by diffusion weighting
- 3.3. Diffusion constant can be obtained from the amount of signal loss but not from the signal intensity
- 3.4. From two measurements, we can obtain a diffusion constant
- 3.5. If there are more than two measurement points, linear least-square fitting is used
- Chapter 4. Principle of diffusion tensor imaging
- 4.1. NMR/MRI can measure diffusion constants along an arbitrary axis
- 4.2. Diffusion sometimes has directionality
- 4.3. Six parameters are needed to uniquely define an ellipsoid
- 4.4. Diffusion tensor imaging characterizes the diffusion ellipsoid from multiple diffusion constant measurements along different directions
- 4.5. Water molecules probe microscopic properties of their environment
- 4.6. Human brain white matter has high diffusion anisotropy
- Chapter 5. Mathematics of diffusion tensor imaging
- 5.1. Our task is to determine six parameters of a diffusion ellipsoid
- 5.2. We can obtain the six parameters from seven diffusion measurements
- 5.3. Determination of the tensor elements from a fitting process
- Chapter 6. Practical aspects of diffusion tensor imaging
- 6.1. Two types of motion artifacts: ghosting and coregistration error
- 6.2. We use echo-planar imaging to perform diffusion tensor imaging
- 6.3. The amount of diffusion-weighting is constrained by the echo time
- 6.4. There are various k-space sampling schemes
- 6.5. Parallel imaging is good news for DTI
- 6.6. Image distortion by eddy current needs special attention
- 6.7. DTI results may differ if spatial resolution and SNR are not the same
- 6.8. Selection of b-matrix
- Chapter 7. New image contrasts from diffusion tensor imaging: theory, meaning, and usefulness of DTI-based image contrast
- 7.1. Two scalar maps (anisotropy and diffusion constant maps) and fiber orientation maps are important outcomes obtained from DTI
- 7.2. Scalar maps (anisotropy and diffusion constant maps) and fiber orientation maps are two important images obtained from DTI
- 7.3. There are tubular and planar types of anisotropy
- 7.4. DTI has several disadvantages
- 7.5. There are multiple sources that decrease anisotropy
- 7.6. Anisotropy may provide unique information
- 7.7. Color-coded maps are a powerful visualization method to reveal white matter anatomy
- Chapter 8. Limitations and improvement of diffusion tensor imaging
- 8.1. Tensor model oversimplifies the underlying anatomy
- 8.2. There are more sophisticated "non-tensor"-based data processing methods, which require different data acquisition protocols
- 8.3. Non-tensor models usually require high b-values
- Chapter 9. Three-dimensional tract reconstruction
- 9.1. Three-dimensional trajectories can be reconstructed from DTI data
- 9.2. There are two types of reconstruction techniques
- 9.3. There are three steps in the tract propagation models
- 9.4. Simple streamline tracking can be used to reconstruct a tract
- 9.5. There are many limitations to simple tract propagation methods
- 9.6. Several approaches are proposed to tackle the limitations
- 9.7. Tract editing uses multiple regions of interest
- 9.8. Brute-force approach is an effective technique for comprehensive tract reconstruction
- 9.9. Accuracy and precision are important factors to be considered
- 9.10. Reproducibility of tractography is measurable
- 9.11. Tractography reveals macroscopic white matter anatomy
- 9.12. There are roughly three types of information obtained from tractography
- 9.13. How can we validate tractography?
- 9.14. How should we use a tool with unknown accuracy?
- 9.15. Quantification is a key to many types of tractography-based studies
- 9.16. There are several possible reasons that lead to smaller (or larger) reconstruction results
- Chapter 10. Quantification approaches
- 10.1. Improvement of conventional quantification approaches
- 10.2. Quantification of anisotropy and tract sizes by DTI
- Chapter 11. Application studies
- 11.1. Background of application studies of DTI
- 11.2. Examples of application studies
- References and Suggested Readings
- Subject Index
