CDF Normalizer (lib)

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Authors

STOKLASA Roman

Year of publication 2025
Type Software
MU Faculty or unit

Faculty of Informatics

web https://cbia.fi.muni.cz/software/cdf-normalizer.html
Description We present a method of image harmonization using Cumulative Distribution Function (CDF) matching based on curve fitting. This approach does not ruin local variability and individual important features. The transformation of image intensities is non-linear but still “smooth and elastic”, as compared to other known histogram matching algorithms. Nonlinear transformation allows for a very good match to the template. At the same time, elasticity constraints help to preserve local variability among individual inputs, which may encode important features for subsequent machine-learning processing. The pre-defined template CDF offers a better and more intuitive control for the input data transformation compared to other methods, especially ML-based ones. Even though we developed our method for MRI images, the method is generic enough to apply to other types of imaging data.
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