pycsemri 0.2.4

A package for CSEMRI with C++ accelerated components.

PyCSEMRI: Python Water-Fat Separation Package for CSE-MRI

Overview

PyWaterFat is a Python package for water-fat separation in Chemical Shift Encoding Magnetic Resonance Imaging (CSE-MRI). This package is based on Diego Hernando's MATLAB fat-water toolbox, with modifications to improve performance and compatibility with Python ecosystems. The confidence map function will be integrated in the near future.

Key Features:

• Implements complex, mixed, and magnitude fitting algorithms for water-fat separation
• No GSL dependency
• Utilizes Eigen C++ library for fast and efficient computations
• Highly portable and easy to install in various environments, including MRI scanners

Background

This package builds upon the work presented at the ISMRM Workshop on Fat-Water Separation: ISMRM Fat-Water Separation Workshop

Dependencies and Licensing

This project utilizes the following third-party libraries for core functionalities:

• Eigen: We use the Eigen library for efficient matrix and vector calculations.

  • Availability: Eigen is an open-source C++ template library for linear algebra, available at https://eigen.tuxfamily.org/.

  • License: Eigen is licensed under the Mozilla Public License, Version 2.0 (MPL 2.0).

• Boost: The Boost C++ Libraries are used in this project specifically for the graph cut algorithm.

  • Availability: The Boost C++ Libraries are a collection of peer-reviewed, portable C++ source libraries, available at https://www.boost.org/.

  • License: Boost is licensed under The Boost Software License.

Please refer to the respective project websites and their associated license files for full details on their terms and conditions.

Installation

This package contains C++ components and requires a compiler for installation from source. However, pre-compiled wheels are provided for common platforms (macOS, Linux), making installation easy via pip.

From PyPI (Recommended for Users)

If you just want to use the package, you can install it directly from the Python Package Index (PyPI). This method will automatically download the correct pre-compiled version for your system.

pip install PyCSEMRI

Usage

A sample code is provided in Example_ChanComb_h5.py.