How to check & fix automatically generated segmentations in large data sets #1
Description
We can start by browsing several brains and take note of segmentation errors (i.e. where either tissue has been classified brain which is actually not part of the brain; or vice versa chunks of tissue might be missing from the segmentation).
A good starting example might be the ABIDE I dataset (Autism Brain Initiative Data Exchange) which you can find on BrainBox here.
We could then choose one brain as an example, and
- build a pool of screenshots of errors which we spot
- find patterns in which regions the algorithms seem to struggle most
- and build our tutorial based on those, for instance
- 'Deleting the meninges from the cortex classification',
- adding screenshots and
- describing how we fix the errors
- which slice view worked best for you (coronal/ sagittal/ axial),
- which pencil size/eraser,
- starting from one end or rather the middle of the brain and everything which you will find useful to add
- and maybe make a video/screencast to show the collaborative & real-time aspect of process
Please join us! Everybody is more than welcome! 🌞