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T2-DWI

This repository provides functions for performing three different model fits to combined T2- and diffusion-weighted (T2-DWI) data acquired using two echo times (TEs) and two b-values:

  1. Two-component model
  2. Bi-exponential model
  3. Mono-exponential apparent diffusion coefficient (ADC)

The method was developed at the MR Cancer group at the Norwegian University of Science and Technology (NTNU) in Trondheim, Norway. https://www.ntnu.edu/isb/mr-cancer

Note

The provided code was developed for research and is not approved for clinical use.

How to cite T2-DWI

In case of using or referring to T2-DWI, please cite it as:

Syversen IF, Elschot M, Sandsmark E, Bertilsson H, Bathen TF, Goa PE. Exploring the diagnostic potential of adding T2 dependence in diffusion-weighted imaging of the prostate. PLoS One. 2021;16(5):e0252387. doi: 10.1371/journal.pone.0252387

How to use T2-DWI

This is a MATLAB® function, and the function was written and tested using MATLAB® R2019b.

To run the functions, type functionName.m(arguments). Note that for all three models, there are certain functions that have to be implemented by the user itself, e.g. for loading of image files.

Two-component model:

Use the calculateTwoComponent.m function, which uses the function hybridfit_TCmodel.m to perform the actual model fit.

Bi-exponential model:

Use the calculateBiExponential.m function, which uses the function hybridfit_BEmodel.m to perform the actual model fit.

Mono-exponential ADC:

Use the calculateADC.m function.

Contact us:

Feel free to contact us: ingrid.f.syversen@ntnu.no