Introduction to Neuroimaging Analysis 1st edition by Mark Jenkinson, Michael Chappell ISBN ‎ 0198816308 ‎ 978-0198816300

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ISBN 10: ‎ 0198816308
ISBN 13: ‎ 978-0198816300
Author: Mark Jenkinson, Michael Chappell

MRI has emerged as a powerful way of studying in-vivo brain structure and function in both healthy and disease states. Whilst new researchers may be able to call upon advice and support for acquisition from operators, radiologists and technicians, it is more challenging to obtain an understanding of the principles of analysing neuroimaging data. This is crucial for choosing acquisition parameters, designing and performing appropriate experiments, and correctly interpreting the results.

This primer gives a general and accessible introduction to the wide array of MRI-based neuroimaging methods that are used in research. Supplemented with online datasets and examples to enable the reader to obtain hands-on experience working with real data, it provides a practical and approachable introduction for those new to the neuroimaging field. The text also covers the fundamentals of what different MRI modalities measure, what artifacts commonly occur, the essentials of the analysis, and common ‘pipelines’ including brain extraction, registration and segmentation.

As it does not require any background knowledge beyond high-school mathematics and physics, this primer is essential reading for anyone wanting to work in neuroimaging or grasp the results coming from this rapidly expanding field.

The Oxford Neuroimaging Primers are short texts aimed at new researchers or advanced undergraduates from the biological, medical or physical sciences. They are intended to provide a broad understanding of the ways in which neuroimaging data can be analyzed and how that relates to acquisition and interpretation. Each primer has been written so that it is a stand-alone introduction to a particular area of neuroimaging, and the primers also work together to provide a comprehensive foundation for this increasingly influential field.

Introduction to Neuroimaging Analysis 1st Table of contents:

1 Introduction

1.1 Main MRI modalities and analysis techniques

1.2 Walk-through of a typical study

Example Box: Look at your data!

Example Box: Keep looking at your data!

Example Box: Think through your analysis early

1.3 MR physics and scanner hardware

Box 1.1: B0 field inhomogeneities

Box 1.2: Resonance frequency

Box 1.3: RF inhomogeneity and bias fields

Box 1.4: Head coils and accelerated imaging

Box 1.5: Gradient fields

1.4 Overview

Summary

Further reading

2 MRI Modalities for Neuroimaging

2.1 Image fundamentals

Box 2.1: Image formats

2.2 Structural MRI

Example Box: SNR, resolution, and acquisition time trade-offs

Example Box: MRI artifacts

Summary

Further reading

2.3 Diffusion MRI

Example Box: Diffusion signal in different tissues

Box 2.2: HARDI

Example Box: Diffusion signal in different tissues (revisited)

Example Box: Viewing diffusion images

Summary

Further reading

2.4 Functional MRI

Box 2.3: T2* Relaxation and BOLD

Summary

Further reading

2.5 Perfusion MRI

Summary

Further reading

2.6 Spectroscopy (MRS)

Summary

Further reading

2.7 Complementary techniques

Summary

Further reading

3 Overview of MRI Analysis

Group Analysis Box

3.1 Early stages

Box 3.1: Voxel and world coordinates

Summary

3.2 Structural pipeline

Example Box: Tissue-type segmentation

Box 3.2: Segmentation of pathological tissue

Example Box: Deep gray matter structure segmentation

Summary

Further reading

3.3 Diffusion pipeline

Box 3.3: Fieldmap acquisitions

Example Box: Correcting for distortions and artifacts in diffusion images

Box 3.4: Diffusion tensor model

Example Box: DTI

Example Box: TBSS

Example Box: Tractography

Summary

Further reading

3.4 Functional pipeline (task and resting state fMRI)

Box 3.5: Motion artifacts

Example Box: Slice timing effects and corrections

Example Box: Aliasing of physiological signals

Example Box: Physiological noise modeling

Example Box: Independent component classification

Example Box: Task fMRI data

Example Box: Resting state fMRI networks

Summary

Further reading

3.5 Perfusion pipeline

Summary

Further reading

4 Brain Extraction

4.1 When it is needed

4.2 Skull stripping versus cortical modeling

Example Box:Brain extraction

4.3 Brain masks

Example Box: Brain masks

4.4 Skull estimation

4.5 Difficulties and troubleshooting

Example Box: Troubleshooting brain extraction

Summary

Further reading

5 Registration

5.1 Spatial transformations

Box 5.1: Transformation parameters, coordinates, and conventions

Example Box: Spatial Transformations

5.2 Cost functions

Box 5.2: Similarity functions

Box 5.3: Intensity models for cost functions

Example Box: Registration

5.3 Resampling and interpolation

Box 5.4: Symmetric registration and halfway spaces

5.4 Case studies

Example Box: Evaluating registrations

Example Box: Registration case studies

5.5 Standard space and templates

5.6 Atlases

Example Box: Probabilistic atlas construction

5.7 Atlas-based segmentation

Summary

Further reading

6 Motion and Distortion Correction

6.1 Motion correction

6.2 Distortion correction

Box 6.1: Gradient-echo fieldmap acquisitions

Box 6.2: Calculating distortion from gradient-echo fieldmaps

Box 6.3: Intensity model for BBR

Box 6.4: Low contrast EPI and registration

Box 6.5: Combining fieldmap-based distortion correction and registration

Example Box: Distortion correction with fieldmaps

Example Box: Distortion correction with blip-up–blip-down data

Summary

Further reading

7 Surface-Based Analysis

7.1 Cortical surface extraction

7.2 Inflated, spherical, and flattened surfaces

7.3 Registration of surface data

7.4 Surface-based fMRI analysis

Summary

Further reading

8 Epilogue

8.1 Planning

8.2 Analysis

8.3 Interpretation

8.4 Next steps

Appendix A: Short Introduction to Brain Anatomy for Neuroimaging

A.1 Brain cells and tissues

A.2 Navigating around brain images

A.3 Brain structures

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Tags: Mark Jenkinson, Michael Chappell, Neuroimaging Analysis