Project-MONAI / Project-MONAI/MONAILabel

Feature request: Support multiple annotations on the same image instance

Open
#787 17 comments 6 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

backlog enhancement
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

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. 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

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.