/Denoising-CEST-MRI

Matlab-based code for denoising MRI-CEST images for improving CEST contrast quantification and pH mapping based on iopamidol.

Primary LanguageMATLABMIT LicenseMIT

What is this repository for?

Demo_Denoising is a collection of Matlab-based scripts for denoising CEST MRI images. Several filters have been provided for denoising MRI-CEST images, including our developed NLmCED filter and several established filters: BM3D, Gaussian and Smoothing Cubic Spline method.

Several Z-spectra datasets have been provided to test the scripts, including:

3 synthetic datasets by simulating Iopamidol at several concentrations, pH values and amplitudes of the semisolid component including ground-truth data and noisy data after applying rician noise at several noise levels

2 in-vitro phantom with Iopamidol at several pH values and concentrations

1 in-vivo datasets with Z-spectra acquired before (PRE) and after (POST) Iopamidol injection in a tumor murine model.

Copyright (c) 2020-2030 University of Al Manar Tunisia, (ENIT), Tunisia and University of Turin (Unito), Italy

All rights reserved. This work should only be used for nonprofit purposes.

Authors: Feriel Romdhane

Installation

Unzip CEST_denoising.zip (contains codes and test data) in a folder that is in the MATLAB path. Demo_CEST_Denoising.m: Demo on how to use the denoising method and data. contrastCEST.m: Function to calculate the CEST Contrast for iopamidol. pH_SyntheticDataset.m: Function to calculate the pH for the synthetic dataset. pH_InVivo.m: Function to calculate the pH for the In Vivo data. psnr_original.m: Function to calculate the PSNR index. ssim_original.m: Function to calculate the SSIM index. BM3D Filter : Folder with BM3D package. NLmCED_Filter: Folder with NLmCED package. dataset_1: Synthetic dataset #1. invitro_1: In-vitro phantom #1. invivo_1: In-vivo data #1.

Instructions to download additional data

To test the additional synthetic dataset #3 and the in-vitro phantom #2:

  1. Access to the XNAT platform of the Molecular Imaging Center of the University of Torino: http://cim-xnat.unito.it with the following credentials: username: CESTMRI password: denoising

  2. Click on the project named CEST-MRI-denoising.

  3. In the Actions Menu on the right panel, click on Manage Files.

  4. A window with a File Manager console will open up, browse in the resource folder named matlab_data to download the data.

Requirements

  1. MS Windows (32 or 64 bit), Linux (32 bit or 64 bit) or Mac OS X (32 or 64 bit)
  2. Matlab R2015a or earlier.

References

[1] F. Romdhane, D. Villano, P. Irrera, L. Consolino, D. L. Longo, "Improving contrast quantification of MRI-CEST images by applying a denoising approach based on a new combination between non-local means filter and anisotropic diffusion tensor," in the 14th European Molecular Imaging Meeting (EMIM), Glasgow, UK, March 2019.

[2] K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, "Image denoising by sparse 3D transform-domain collaborative filtering," IEEE Trans. Image Process., vol. 16, no. 8, August 2007.

[3] DL.Longo, W. Dastru W, G. Digilio, J. Keupp, S. Langereis, S. Lanzardo, S. Prestigio, O. Steinbach, E.Terreno, F. Uggeri, S. Aime, "Iopamidol as a responsive MRI-chemical exchange saturation transfer contrast agent for pH mapping of kidneys: In vivo studies in mice at 7 T," Magn Reson Med 2011;65(1):202-211.s

Citation

Cite the code: DOI

Cite the paper: https://doi.org/10.1002/mrm.28676

Who do I talk to?

If you have any comment, suggestion, or question, please do contact Feriel Romdhane at ferielromdhane@yahoo.fr