wsimson tristan-deep commited on
Commit
094c158
·
1 Parent(s): 0877eb3

Data card: remove early-access notice, add website and GitHub badges (#88)

Browse files

- Remove early-access notice from README (5bf77b36670e3f01157d3e1c2f28695e529f56cf)
- Add website and GitHub badges and link the dataset catalog (bbceb057a9624dfc594066816d2fa6af6799a01f)


Co-authored-by: Tristan Stevens <tristan-deep@users.noreply.huggingface.co>

README.md CHANGED
@@ -11,13 +11,16 @@ viewer: false
11
 
12
  ![Collage of reconstructed images and raw channel data from the OpenH-RF subsets](assets/collage.webp)
13
 
14
- ℹ️ This repository is currently available in early access to project contributors.
 
 
 
15
 
16
  ## Dataset Description
17
 
18
  OpenH-RF is a community-driven dataset initiative building the open, shared foundation needed to train and evaluate AI models built on pre-beamformed (channel capture) medical ultrasound measurements.
19
 
20
- This dataset is a collection of RF samples and metadata in the [`zea` file format](https://github.com/tue-bmd/zea) from a variety of tasks and applications, including ultrasound localization microscopy, ultrasound computer tomography, b-mode, flow imaging and more.
21
 
22
  Each subdirectory here holds a data card and a processing pipeline. The matching reconstruction scripts, one runnable reference reconstruction per subset, are in the companion repository, [github.com/open-h/OpenH-RF](https://github.com/open-h/OpenH-RF).
23
 
 
11
 
12
  ![Collage of reconstructed images and raw channel data from the OpenH-RF subsets](assets/collage.webp)
13
 
14
+ <p align="center">
15
+ <a href="https://open-h.github.io/OpenH-RF/"><img src="assets/badge-website.svg" alt="Website" style="display: inline; margin: 0 3px;"></a>
16
+ <a href="https://github.com/open-h/OpenH-RF"><img src="assets/badge-github.svg" alt="GitHub" style="display: inline; margin: 0 3px;"></a>
17
+ </p>
18
 
19
  ## Dataset Description
20
 
21
  OpenH-RF is a community-driven dataset initiative building the open, shared foundation needed to train and evaluate AI models built on pre-beamformed (channel capture) medical ultrasound measurements.
22
 
23
+ This dataset is a collection of RF samples and metadata in the [`zea` file format](https://github.com/tue-bmd/zea) from a variety of tasks and applications, including ultrasound localization microscopy, ultrasound computer tomography, b-mode, flow imaging and more. The dataset catalog and gallery is available at [open-h.github.io/OpenH-RF](https://open-h.github.io/OpenH-RF).
24
 
25
  Each subdirectory here holds a data card and a processing pipeline. The matching reconstruction scripts, one runnable reference reconstruction per subset, are in the companion repository, [github.com/open-h/OpenH-RF](https://github.com/open-h/OpenH-RF).
26
 
assets/badge-github.svg ADDED
assets/badge-website.svg ADDED
assets/logo-badge-white.svg ADDED