Project-MONAI / Project-MONAI/MONAI
Whole slide dataset to extract random patches
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- Dominant language
- Python
- Stars
- 8.7k
- Forks
- 1.6k
- Avg merge
- 5d 1h
- Merged PRs (30d)
- 20
Description
Currently, PatchWSIDataset generates patches based on pre-defined locations. In digital pathology use cases, there is a need for generating such patches randomly from all over the whole slide image. This requirement is different than using TileOnGrid to generate such patches since this transform is operating on the image in the memory while RandPatchWSIDataset directly deal with whole slide images on the file system.
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
Start by reading the existing PatchWSIDataset implementation and the TileOnGrid transform to understand their boundaries. Determine how a proposed RandPatchWSIDataset should sample patches from whole-slide image files rather than in-memory images, and identify the relevant dataset tests or examples. Done means the random whole-slide sampling behavior is implemented and covered by tests.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100