Project-MONAI / Project-MONAI/MONAILabel
Feature request: Support multiple annotations on the same image instance
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 891
- Forks
- 269
- Avg merge
- 15h 41m
- Merged PRs (30d)
- 1
Description
To create high-quality datasets, it is necessary to have the same image annotated multiple times by different people (e.g. double or triple segmentations). At the moment there is no interface for this in MONAILabel.
My team could also contribute to this, but I am not sure what is the best way to implement this feature. Certainly some changes need to be made to the datastore, filter functions and plugins. Also some sort of user management is then necessary.
Currently, for multiple annotations, we use a workaround with multiple instances of MONAILabel sharing the same app. Each instance is then used by a different annotator. Later, the data must then be merged in a cumbersome way.
I would prefer that this functionality be integrated into MONAILabel in a bundled way. I am relatively sure that other teams will need this feature as well (@LilianaCaldeira, @dtruhn, @kbressem).
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No files, tests, or entry points are named. Start by mapping how the datastore, filter functions, plugins, and annotation workflow represent an image instance and annotator; then clarify the user-management and data-model decisions with maintainers. Done should include an agreed design and integrated support for multiple annotations without separate MONAI Label instances.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- backend, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100