| Preface | p. ix |
| Basics of diffusion measurement | p. 1 |
| NMR spectroscopy and MRI can detect signals from water molecules | p. 1 |
| What is diffusion? | p. 3 |
| How to measure diffusion? | p. 4 |
| Anatomy of diffusion measurement | p. 13 |
| A set of unipolar gradients and spin-echo sequence is most widely used for diffusion weighting | p. 13 |
| There are four parameters that affect the amount of signal loss | p. 13 |
| There are several ways of achieving a different degree of diffusion weighting | p. 17 |
| Mathematics of diffusion measurement | p. 19 |
| We need to calculate distribution of signal phases by molecular motion | p. 19 |
| Simple exponential decay describes signal loss by diffusion weighting | p. 27 |
| Diffusion constant can be obtained from the amount of signal loss but not from the signal intensity | p. 27 |
| From two measurements, we can obtain a diffusion constant | p. 30 |
| If there are more than two measurement points, linear least-square fitting is used | p. 31 |
| Principle of diffusion tensor imaging | p. 33 |
| NMR/MRI can measure diffusion constants along an arbitrary axis | p. 33 |
| Diffusion sometimes has directionality | p. 33 |
| Six parameters are needed to uniquely define an ellipsoid | p. 35 |
| Diffusion tensor imaging characterizes the diffusion ellipsoid from multiple diffusion constant measurements along different directions | p. 37 |
| Water molecules probe microscopic properties of their environment | p. 39 |
| Human brain white matter has high diffusion anisotropy | p. 40 |
| Mathematics of diffusion tensor imaging | p. 41 |
| Our task is to determine six parameters of a diffusion ellipsoid | p. 41 |
| We can obtain the six parameters from seven diffusion measurements | p. 43 |
| Determination of the tensor elements from a fitting process | p. 45 |
| Practical aspects of diffusion tensor imaging | p. 49 |
| Two types of motion artifacts: ghosting and coregistration error | p. 49 |
| We use echo-planar imaging to perform diffusion tensor imaging | p. 51 |
| The amount of diffusion-weighting is constrained by the echo time | p. 53 |
| There are various k-space sampling schemes | p. 53 |
| Parallel imaging is good news for DTI | p. 57 |
| Image distortion by eddy current needs special attention | p. 60 |
| DTI results may differ if spatial resolution and SNR are not the same | p. 61 |
| Selection of b-matrix | p. 63 |
| New image contrasts from diffusion tensor imaging: theory, meaning, and usefulness of DTI-based image contrast | p. 69 |
| Two scalar maps (anisotropy and diffusion constant maps) and fiber orientation maps are important outcomes obtained from DTI | p. 69 |
| Scalar maps (anisotropy and diffusion constant maps) and fiber orientation maps are two important images obtained from DTI | p. 70 |
| There are tubular and planar types of anisotropy | p. 72 |
| DTI has several disadvantages | p. 75 |
| There are multiple sources that decrease anisotropy | p. 76 |
| Anisotropy may provide unique information | p. 79 |
| Color-coded maps are a powerful visualization method to reveal white matter anatomy | p. 83 |
| Limitations and improvement of diffusion tensor imaging | p. 85 |
| Tensor model oversimplifies the underlying anatomy | p. 85 |
| There are more sophisticated "non-tensor"-based data processing methods, which require different data acquisition protocols | p. 87 |
| Non-tensor models usually require high b-values | p. 90 |
| Three-dimensional tract reconstruction | p. 93 |
| Three-dimensional trajectories can be reconstructed from DTI data | p. 93 |
| There are two types of reconstruction techniques | p. 93 |
| There are three steps in the tract propagation models | p. 94 |
| Simple streamline tracking can be used to reconstruct a tract | p. 95 |
| There are many limitations to simple tract propagation methods | p. 99 |
| Several approaches are proposed to tackle the limitations | p. 100 |
| Tract editing uses multiple regions of interest | p. 106 |
| Brute-force approach is an effective technique for comprehensive tract reconstruction | p. 110 |
| Accuracy and precision are important factors to be considered | p. 110 |
| Reproducibility of tractography is measurable | p. 113 |
| Tractography reveals macroscopic white matter anatomy | p. 114 |
| There are roughly three types of information obtained from tractography | p. 115 |
| How can we validate tractography? | p. 117 |
| How should we use a tool with unknown accuracy? | p. 119 |
| Quantification is a key to many types of tractography-based studies | p. 120 |
| There are several possible reasons that lead to smaller (or larger) reconstruction results | p. 121 |
| Quantification approaches | p. 125 |
| Improvement of conventional quantification approaches | p. 125 |
| Quantification of anisotropy and tract sizes by DTI | p. 130 |
| Application studies | p. 149 |
| Background of application studies of DTI | p. 149 |
| Examples of application studies | p. 150 |
| References and Suggested Readings | p. 163 |
| Subject Index | p. 175 |
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