tensorflow / tensorflow/datasets
[data request] CT Lymph Nodes
Open
Nobody has claimed this yet.
dataset request
- Dominant language
- Python
- Stars
- 4.6k
- Forks
- 1.6k
- Avg merge
- 3h 54m
- Merged PRs (30d)
- 1
Description
- Name of dataset: CT Lymph Nodes
- URL of dataset: https://wiki.cancerimagingarchive.net/display/Public/CT+Lymph+Nodes
- License of dataset: Creative Commons Arribution 3.0 Unported License
- Short description of dataset and use case(s): This dataset contains 110,013 Computed Tomography (CT) images of the mediastinum and abdomen in which lymph node positions are marked by radiologists at the National Institutes of Health, Clinical Center. 388 mediastinal lymph nodes come from 90 patients and a total of 595 abdominal lymph nodes in 86 patients in this dataset. This collection could be useful to develop an automated detection of lymph nodes and could be an important clinical diagnostic tool.
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, the guide linked in the issue, to understand how TFDS dataset contributions are structured. Confirm the CT Lymph Nodes dataset details and license from the provided URL, then follow the guide; done means the dataset is contributed in the repository according to those instructions.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, tensorflow
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100