tensorflow / tensorflow/datasets
[data request]KiTS19
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dataset request
- Dominant language
- Python
- Stars
- 4.6k
- Forks
- 1.6k
- Avg merge
- 3h 54m
- Merged PRs (30d)
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Description
- Name of dataset: 2019 Kidney and Kidney Tumor Segmentation (Kits19)
- URL of dataset: https://kits19.grand-challenge.org/data/
- License of dataset: MIT License
- Short description of dataset and use case(s): This dataset is for 2019 Kidney and Kidney Tumor Segmentation Challenge. This dataset has CT scan images of patients who have Kidney Tumor. This dataset includes a training data of 210 patients and a test data of 90 patients. Automatic semantic segmentation of kidneys and kidney tumors is a promising tool towards automatically quantifying a wide array of morphometric features, but no sizeable annotated dataset is currently available to train models for this task.
For more information please refer to this paper: https://arxiv.org/abs/1904.00445
Folks who would also like to see this dataset in tensorflow/datasets, please thumbs-up so the developers can know which requests to prioritize.
And if you'd like to contribute the dataset (thank you!), see our guide to adding a dataset.
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 with docs/add_dataset.md, then review the Kits19 dataset details at the linked challenge page and paper. Done means contributing Kits19 to tensorflow/datasets according to the repository guide.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, tensorflow
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100