Multi_TE_UTE_Simulation

Multi-TE Lung T2* Decay Simulation

This repository contains MATLAB code for simulating multi-TE lung T2* decay using modified 3D Shepp-Logan phantoms. The simulation workflow is described below:

Simulation Workflow:

1. Phantom Generation: Modified 3D Shepp-Logan phantoms with isotropic matrix sizes of 64x64x64, 96x96x96, or 128x128x128 is created. The signal intensity pattern of the phantom resembles SNR patterns observed from murine lungs in vivo.

2. T2 Relaxation Modeling*: T2* relaxation was incorporated into the signal decay during both the nominal echo time and the radial readout. Lung parenchyma was assigned a T2* value of 0.40 ms, and vasculature was assigned a T2* value of 3.16 ms.

3. Signal Decay Equation: The image signal was varied at the voxel level using the signal decay equation:

   S(k,i) = S0 * exp(-(TE(k)+(i-1)td)/T2*

   where:

   • (S(k,I)) is the signal at voxel (i) and echo time (k).
   • (S0) is the initial signal without decay.
   • (TE) are the nominal echo times.
   • (i) is the index of the number of points along the radial projections.
   • (td) is the dwell time.

4. K-Space Data Generation: For each unique combination of echo time and radial projection, k-space data were generated by performing a Fast Fourier Transform (FFT) of the signal-decayed images. Golden angle sampling was used to create radial FIDs.

5. Noise Addition: Gaussian noise was added separately to the real and imaginary portions of the complex k-space data to generate noisy FIDs, simulating image SNR levels typically observed in fully sampled, in-vivo mouse lung images.

6. Image Reconstruction: Images were reconstructed from noisy FIDs data and prescribed trajectories using Cartesian re-gridding, iterative density compensation, and FFT.

How to Run the Simulation:

To run the simulation, execute the file named "main" in MATLAB.

For any questions or issues, please contact Abdullah S. Bdaiwi at abdullah.bdaiwi@cchmc.org.