Neuroimaging and Data Science

Neuroimaging and Data Science

Preliminaries

Preface

Introduction

1. About this book

The data science toolbox

2. The Unix operating system
3. Version control
4. Computational environments and computational containers

Programming

5. A brief introduction to Python
6. The Python environment
7. Sharing code with others

Scientific computing

8. The scientific Python ecosystem
9. Manipulating tabular data with Pandas
10. Visualizing data with Python

Neuroimaging in Python

11. Data science tools for neuroimaging
12. Reading neuroimaging data with Nibabel
13. Using nibabel to align different measurements

Image processing

14. Image processing
15. Image segmentation
16. Image registration

Machine learning

17. The core concepts of machine learning
18. The Scikit-learn package
19. Overfitting
20. Validation
21. Model selection
22. Deep learning

Appendices

23. Solutions to exercises
24. ndslib function reference

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By Ariel Rokem & Tal Yarkoni
© Copyright 2021.