Welcome to Monalisa’s documentation!

• Quick Start
  • Hello Monalisa
  • Installation
    • Clone the Repository
    • Set Up a c++ Compiler
    • Add Monalisa source path to your MATLAB path
    • Compile the C++ Source
    • Verify Installation
    • Notes
• Contents
  • Introduction
    • The Design of Monalisa
    • A few Definitions
    • A Quick View at the List of our Reconstructions
  • Reconstruction Calls
    • Input Arguments for Reconstruction Functions
    • Non-Cartesian Static Reconstructions
    • Deformation-Fields
    • Non-Cartesian Chain Reconstructions
    • Non-Cartesian Sheet Reconstructions
    • Partial-Cartesian Static Reconstructions
    • Partial-Cartesian Chain Reconstructions
  • The Mitosius
    • Prerequisites
    • Usage instructions
    • Notes
    • Using a Custom Acquisition Trajectory
  • Binning: Flexible Readout Rearrangement
    • First Example: Sequential Binning
    • Second Example: Task-Based (Hi-Fi) fMRI
    • Third Example: Respiratory Binning for Motion-Resolved Cardiac MRI using Superior-Inferior (SI) Projections
    • Fourth Example: Cardiac Binning for Motion-Resolved Cardiac MRI using Superior-Inferior (SI) Projections
  • Coil Sensitivity Map Estimation
    • Coil sensitivity from pre-scan images
    • Coil sensitivity from raw data pre-scans
    • Automated Estimation
    • Manual Estimation
    • Code Explanation
  • Acquisition Guidelines for Coil Sensitivity Estimation using Prescans
• Examples
  • Tutorial 1: Reconstruct MRI rawdata
    • Step 1: Compute Coil Sensitivity
    • Step 2: Binning
    • Step 2.1: allLines Binning - A Single Bin
    • Step 2.2: Sequential Binning - 5-Second Temporal Bins
    • Step 3: Preparing the Data for Reconstruction (Mitosius)
    • Efficient Workflow: Local Preprocessing, HPC Reconstruction
    • Step 4: Running Reconstructions

• API

• Docker for Monalisa
  • Dockerfile Setup
  • License Requirements
  • Steps to Run Monalisa
• Acknowledgment and Authors
  • Cite the Article
  • Reference the Repository and SOPs
  • Contact for Significant Advancements or Commercial Use
    • The contributors behind Monalisa
    • Acknowledgements
• Discussion
  • Sketching a Classical Thermodynamic Theory of Information for MRI Reconstructions
    • Introduction
    • Iterative Reconstructions
    • The Phase Space
    • The Space of Memory States
    • The Heat Engine
    • The Computer as an Engine
    • A Postulate for the Thermodynamical Entropy of the Dynamic Memory
    • Information and Efficiency
    • Connection with the Theory of Information
    • Parallel Computing
    • Connection with the Landauer’s Principle
    • Connection with Statistical Mechanic
    • Artificial Intelligence as an Amplification of Efficiency
    • Conclusion

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