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semiQ is a software package designed to calculate the five new semi-quantitative quantifiers described in the following article: "Bridging the Gap between Clinical and Quantitative MRI". It contains example data from both phantoms and humans.

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semiQ

semiQ is a software package designed to calculate the five new semi-quantitative quantifiers described in the following article: "Bridging the Gap between Clinical and Quantitative MRI". It contains example data from both phantoms and humans. For more information, please contact:

Aviv Mezer: aviv.mezer(AT)elsc.huji.ac.il

Shachar Moskovich: shachar.moskovich(AT)mail.huji.ac.il

Phantoms

  • phantoms_run_args.mat contains all arguments needed to produce the new quantifiers, as well as the synthetic quantifiers, using the phantom_run function.
  • phantom_run expands the input table T that contains the different values of different lipids.

Humans

  • division_imgs is a function used to produce 3 division images, T1w/T2w, T1w/PDw and ln(T1w/PDw), using 3 weighted images (T1w, T2w, and PDw), as well as a brain mask.
  • correlation_example is a script that calculates the correlations between different quantifiers and quantitative maps, for a single subject. It calls another function, cutoff_mask, which is used to remove extreme values from the quantifiers and the maps.
  • relaxivity_example is a script that calculates the relaxivity between quantitative maps, as well as the semi-quantitative relaxivities, using a modified version of MDM_toolbox (https://github.com/shirfilo/MDM_toolbox/tree/master, Shir Filo). It uses the function calc_slopes, which calls the function calc_slopes_fit_manual_bins, which bins the values of the input images using slope_bin function.
  • Example_data contains the data of a single subject: T1w, T2w, PDw, R1, R2, PD, seg, mask and the TEs in which the T2w and PDw images were parcelled with.

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(C) Mezer lab, the Hebrew University of Jerusalem, Israel, Copyright 2023

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semiQ is a software package designed to calculate the five new semi-quantitative quantifiers described in the following article: "Bridging the Gap between Clinical and Quantitative MRI". It contains example data from both phantoms and humans.

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