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  • 1. Installation and Background »
  • 1.1. Install AFNI on Your Own Computer

1.1. Install AFNI on Your Own Computer¶

  • 1.1.1. Overview
  • 1.1.2. Linux, Ubuntu 24.04
  • 1.1.3. Linux, Ubuntu 22.04
  • 1.1.4. Linux, Ubuntu 20.04
  • 1.1.5. Linux, Fedora
  • 1.1.6. Linux, Rocky
  • 1.1.7. Linux, Red Hat and CentOS
  • 1.1.8. macOS 12+ (Apple Silicon/ARM processor/chip: M1, M2, …)
  • 1.1.9. macOS 12+ (Intel processor/chip)
  • 1.1.10. Windows 10: Windows Subsystem for Linux (WSL)
  • 1.1.11. Installation notes for older operating systems

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Table of Contents

  • 1. Installation and Background
    • 1.1. Install AFNI on Your Own Computer
      • 1.1.1. Overview
      • 1.1.2. Linux, Ubuntu 24.04
      • 1.1.3. Linux, Ubuntu 22.04
      • 1.1.4. Linux, Ubuntu 20.04
      • 1.1.5. Linux, Fedora
      • 1.1.6. Linux, Rocky
      • 1.1.7. Linux, Red Hat and CentOS
      • 1.1.8. macOS 12+ (Apple Silicon/ARM processor/chip: M1, M2, …)
      • 1.1.9. macOS 12+ (Intel processor/chip)
      • 1.1.10. Windows 10: Windows Subsystem for Linux (WSL)
      • 1.1.11. Installation notes for older operating systems
    • 1.2. Install AFNI on Administered Systems
    • 1.3. Work with Docker/Containerized AFNI
    • 1.4. Download other/specific AFNI/SUMA software
    • 1.5. Prep for Bootcamp
    • 1.6. Miniconda: Python(s) in a convenient setup
  • 2. Starting with AFNI
  • 3. Educational resources
  • 4. All program helps
  • 5. AFNI GUI (afni)
  • 6. SUMA GUI (suma)
  • 7. FATCAT
  • 8. NIFTI
  • 9. Statistics
  • 10. Templates & Atlases
  • 11. Non-human processing
  • 12. Tutorials, Examples
  • 13. Demo Material
  • 14. Codex: AFNI Code Examples from publications
  • 15. Citations and Reference Works
  • 16. Developer Documentation
  • 17. Contributors
  • 18. Glossary
  • 19. Main AFNI pages

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