Developer: Jia Xu, PhD
Name of software: pyAMARES, an Open-Source Python Library for Fitting Magnetic Resonance Spectroscopy Data
Languages: Python
Abstract: PyAMARES is an open-source Python implementation of AMARES (Advanced Method for Accurate, Robust, and Efficient Spectral Fitting) for quantifying magnetic resonance spectroscopy (MRS) data. The software features an intuitive spreadsheet-based (Excel) interface for managing prior knowledge and fitting parameters, making it easy to fix or fit any spectral parameters. PyAMARES integrates seamlessly with the Python ecosystem and can function as either a standalone program or a third-party library. Beyond traditional AMARES capabilities, the software offers advanced features including fitting without prior knowledge using HSVD initialization, multiprocessing for efficient batch analysis, and frequency-selective fitting. Comprehensive documentation and step-by-step tutorials are available at pyamares.readthedocs.io. The tutorials are provided as Jupyter notebooks, which can be run directly in web browsers through platforms like Google Colab, allowing users to explore pyAMARES without local installation.
Credit: Please cite the publication mentioned below if you use pyAMARES.
Contact: jia-xu-1@uiowa.edu
Publication: Xu J, Vaeggemose M, Schulte RF, Yang B, Lee CY, Laustsen C, Magnotta VA. PyAMARES, an Open-Source Python Library for Fitting Magnetic Resonance Spectroscopy Data. Diagnostics. 2024;14(23):2668.
URL: https://github.com/HawkMRS/pyAMARES
Documentation: https://pyamares.readthedocs.io/