Niviz: Configurable quality control image generation and rating
Jerrold Jeyachandra @jerdra
The process of QCing is universally boring, terrible and inefficient.
Most pipelines people write and use don’t generate QC images, especially those that are as user-friendly as widely established pipelines such as fMRIPREP
Even then, the QC images that are generated do not necessarily match how users end up QC’ing and rating images.
Most of the time users must figure out their own way to record and organize their QC results, this is incredibly variable across individuals. Your collaborator might use differing definitions, organizational principles, and file formats for storing their QC results than you.
Comparing rated images is often slow, manual and therefore painful. Often-times users have doubt about their ratings and would want to compare it to other images with the same rating. Doing this is often a very manual process (i.e lookup similar QC ratings on your spreadsheet, find file, open both images and compare)
Niviz is a simple, configurable Python-based tool that:
niviz-raterthat collects generated QC images (or any set of images organized in a BIDS-style dataset!!!) into an interactive QC interface. In addition, QC can be configured to suit the user’s needs using (yet another) simple YAML file.
Both niviz and niviz-rater are relatively new projects and therefore require a bit of maintenance and organizational effort. The primary goals are as follows:
Issues can be found under:
Look for the
good first issue label for easy topics!
We’ll probably create our own channel if this picks up interest :)
Familiarity with Svelte framework is preferred. I’m still learning myself!
Depending on which repository you contribute to:
Bottlefor building python web applications
As part of contributing to the documentation efforts of this project, we’d like to host some OSF sample data.
Some image data from a pipeline like fMRIPrep
Some QC image data so that users can play around with writing a YAML specification file and using the QC interface
Project contributers will be included using the GitHub allcontributors bot. I’m still setting this up 🙈
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coding_methods, documentation, visualization
DWI, fMRI, MRI
Hi @brainhackorg/project-monitors my project is ready!