Data processing algorithms for tomography

Welcome to Algotom’s documentation about data processing algorithms for tomography. This documentation is not only to explain functions available in the Algotom package but also to present tomography-related tutorials, technical notes, and applications.

Source code: https://github.com/algotom/algotom

Table of Contents

• 1. Basic tutorials
  • 1.1. Python for tomography scientists as beginners
    • 1.1.1. Installing Python and tools for writing codes
    • 1.1.2. Python ecosystem of libraries
    • 1.1.3. Where/how to start coding
  • 1.2. Common data format at synchrotron facilities
    • 1.2.1. Hdf format
    • 1.2.2. Tiff format
  • 1.3. Basic components of an X-ray tomography system
    • 1.3.1. How tomography works
    • 1.3.2. Basic components of an X-ray tomography system
  • 1.4. Basic workflow for processing tomographic data
    • 1.4.1. Read/write data
    • 1.4.2. Flat-field correction
    • 1.4.3. Zinger removal
    • 1.4.4. Ring artifact removal
    • 1.4.5. Center-of-rotation determination
    • 1.4.6. Denoising or contrast enhancement
    • 1.4.7. Image reconstruction
    • 1.4.8. Other data processing steps
  • 1.5. Parallel processing in Python
• 2. Features and capabilities
• 3. Installation
  • 3.1. Using conda
  • 3.2. Using pip
  • 3.3. From source
  • 3.4. Notes
• 4. Demonstrations
  • 4.1. Setting up a Python workspace
  • 4.2. Exploring raw data and making use of the input-output module
    • 4.2.1. Nxs/hdf files
    • 4.2.2. Tiff files
    • 4.2.3. Mrc files
    • 4.2.4. Other file formats
  • 4.3. Methods and tools for removing ring artifacts
    • 4.3.1. Improvements
    • 4.3.2. Tools for designing ring removal methods
  • 4.4. Comparison of ring removal methods on challenging sinograms
    • 4.4.1. Same sample-type and slice but different in shape
    • 4.4.2. Partial ring artifacts
    • 4.4.3. All types of ring artifacts
    • 4.4.4. Having valid stripes (not artifacts)
    • 4.4.5. For cone-beam tomography
• 5. Technical notes
  • 5.1. Implementations of X-ray speckle-based phase-contrast tomography
    • 5.1.1. Introduction
    • 5.1.2. Data acquisition
    • 5.1.3. Data processing
    • 5.1.4. Implementation
    • 5.1.5. Demonstration
• 6. Update notes
• 7. API Reference
  • 7.1. Input-output
    • 7.1.1. algotom.io.converter
    • 7.1.2. algotom.io.loadersaver
  • 7.2. Pre-processing
    • 7.2.1. algotom.prep.calculation
    • 7.2.2. algotom.prep.conversion
    • 7.2.3. algotom.prep.correction
    • 7.2.4. algotom.prep.filtering
    • 7.2.5. algotom.prep.removal
    • 7.2.6. algotom.prep.phase
  • 7.3. Reconstruction
    • 7.3.1. algotom.rec.reconstruction
  • 7.4. Post-processing
    • 7.4.1. algotom.post.postprocessing
  • 7.5. Utilities
    • 7.5.1. algotom.util.calibration
    • 7.5.2. algotom.util.simulation
    • 7.5.3. algotom.util.utility
    • 7.5.4. algotom.util.correlation
• 8. Credits
  • 8.1. Citations
  • 8.2. References
• 9. Highlights