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Welcome to the cleanX wiki!

cleanX is a Python library that is meant to help people do data cleaning and preparation of large sets of radiology images. Functions for exploratory data analysis, data cleaning, normalization and augmentation are included. The library began in April 2021.

The library hopes to help overcome certain misunderstandings between medical professionals and engineers. For example, engineers often do not understand that you can not augment medical images in certain ways, as you would the image of a cat, without the resulting image taking on a different clinical meaning. On the other hand, many medical professionals lack coding skills. While using the library obviously requires code, it turns some complex code maneuvers into single functions, or in the lingo 'high-level APIs.'

In order to make the library even more useful, we are working on a no-code workflow in addition to adding functions. For a demo of a possible workflow with code go to the workflow_demo folder and examine the notebook within.

The project has a conda based version. Documentation is best to build on command. Please see the notes here.

If you have ideas or comments on the library you can open a ticket and/or email ([email protected]).