GASP: Generation of Arbitrary Spectral Profiles

Overview

GASP (Generation of Arbitrary Spectral Profiles) is a Python library for simulating and analyzing MRI sequences, particularly focused on balanced Steady-State Free Precession (bSSFP) and spectral shaping techniques. This project provides tools for simulating MRI signals, generating phantoms, and applying the GASP method to achieve desired spectral profiles.

Features

• Simulation of bSSFP sequences
• Generation of various phantom types (e.g., Shepp-Logan, circles, blocks)
• Implementation of the GASP method for spectral shaping
• Tools for analyzing and visualizing MRI data
• Support for different tissue types and their relaxation properties

Development

This project requires python 3.8+ and has the following dependancies: numpy matplotlib scikit-image seaborn pymapvbvd jupyterlab gdown scipy

To setup a local python enviroment with conda:

Create a new conda environment from scatch

conda create -n gasp python=3.8 
conda activate gasp

Then install packages with pip:

pip install numpy matplotlib scikit-image seaborn pymapvbvd jupyterlab gdown scipy

Usage

Here's a basic example of how to use the GASP simulation:

from gasp import simulation, responses

# Set up simulation parameters
width, height = 256, 256
npcs = 16
TRs = [5e-3, 10e-3, 20e-3]
alpha = np.deg2rad(60)
gradient = 2 * np.pi

# Create a desired spectral profile
D = responses.gaussian(width, bw=0.2, shift=0)

# Simulate GASP
Ic, M, An = simulation.simulate_gasp(D, width, height, npcs, TRs, alpha, gradient)

# Visualize results
simulation.view_gasp_results(Ic, M, D)

Modules

• analysis.py: Contains functions for analyzing GASP results and Dixon methods
• dataloader.py: Handles loading of raw MRI data
• dataset.py: Provides functions to load specific datasets
• gasp.py: Core implementation of the GASP method
• phantom.py: Functions for generating various phantom types
• responses.py: Implements different spectral response functions
• simulation.py: Main simulation routines for bSSFP and GASP
• ssfp.py: Implementation of Steady-State Free Precession signal equations
• tissue.py: Defines tissue properties and generates tissue phantoms
• view.py: Visualization tools for 3D data