Add website and GitHub badges and link the dataset catalog

Centered Website and GitHub badges below the collage, and a link to the dataset catalog and gallery in the description.

README.md

@@ -11,11 +11,16 @@ viewer: false
 
 ![Collage of reconstructed images and raw channel data from the OpenH-RF subsets](assets/collage.webp)
 
+<p align="center">
+  <a href="https://open-h.github.io/OpenH-RF/"><img src="assets/badge-website.svg" alt="Website" style="display: inline; margin: 0 3px;"></a>
+  <a href="https://github.com/open-h/OpenH-RF"><img src="assets/badge-github.svg" alt="GitHub" style="display: inline; margin: 0 3px;"></a>
+</p>
+
 ## Dataset Description
 
 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.
 
-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.
+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).
 
 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).