diff --git a/docs/using/selecting.md b/docs/using/selecting.md
index 354f818317..4f31292c3a 100644
--- a/docs/using/selecting.md
+++ b/docs/using/selecting.md
@@ -328,13 +328,16 @@ See the [contributing guide](../contributing/stacks.md) for information about ho
 
 ### Other GPU-accelerated notebooks
 
-| Flavor             | Description                                                                                                                                                                                                                                                                                                                                                  |
-| ------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
-| [GPU-Jupyter][gpu] | Power of your NVIDIA GPU and GPU calculations using Tensorflow and Pytorch in collaborative notebooks. This is done by generating a Dockerfile that consists of the **nvidia/cuda** base image, the well-maintained **docker-stacks** that is integrated as a submodule, and GPU-able libraries like **Tensorflow**, **Keras** and **PyTorch** on top of it. |
-| [PRP-GPU][prp_gpu] | PRP (Pacific Research Platform) maintained [registry][prp_reg] for jupyter stack based on NVIDIA CUDA-enabled image. Added the PRP image with Pytorch and some other Python packages and GUI Desktop notebook based on <https://github.com/jupyterhub/jupyter-remote-desktop-proxy>.                                                                         |
-| [b-data][b-data]   | GPU accelerated, multi-arch (`linux/amd64`, `linux/arm64/v8`) docker images for [R][r_cuda], [Python][python_cuda] and [Julia][julia_cuda]. Derived from nvidia/cuda `devel`-flavored images, including TensortRT and TensorRT plugin libraries. With [code-server][code-server] next to JupyterLab. Just Python – no [Conda][conda]/[Mamba][mamba].         |
+| Flavor                            | Description                                                                                                                                                                                                                                                                                                                                                  |
+| --------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| [GPU-Jupyter][gpu]                | Power of your NVIDIA GPU and GPU calculations using Tensorflow and Pytorch in collaborative notebooks. This is done by generating a Dockerfile that consists of the **nvidia/cuda** base image, the well-maintained **docker-stacks** that is integrated as a submodule, and GPU-able libraries like **Tensorflow**, **Keras** and **PyTorch** on top of it. |
+| [myLab TH Lübeck Images][gpu_thl] | Images based on the **jupyter/docker-stacks**, built and maintained at the [myLab TH Lübeck][gpu_mylab] using build scripts similar to iot-salzburg. Several images include GPU libraries.                                                                                                                                                                   |
+| [PRP-GPU][prp_gpu]                | PRP (Pacific Research Platform) maintained [registry][prp_reg] for jupyter stack based on NVIDIA CUDA-enabled image. Added the PRP image with Pytorch and some other Python packages and GUI Desktop notebook based on <https://github.com/jupyterhub/jupyter-remote-desktop-proxy>.                                                                         |
+| [b-data][b-data]                  | GPU accelerated, multi-arch (`linux/amd64`, `linux/arm64/v8`) docker images for [R][r_cuda], [Python][python_cuda] and [Julia][julia_cuda]. Derived from nvidia/cuda `devel`-flavored images, including TensortRT and TensorRT plugin libraries. With [code-server][code-server] next to JupyterLab. Just Python – no [Conda][conda]/[Mamba][mamba].         |
 
 [gpu]: https://github.com/iot-salzburg/gpu-jupyter
+[gpu_thl]: https://hub.docker.com/r/hanseware/jhub-images
+[gpu_mylab]: https://mylab.th-luebeck.de
 [prp_gpu]: https://gitlab.nrp-nautilus.io/prp/jupyter-stack/-/tree/prp
 [prp_reg]: https://gitlab.nrp-nautilus.io/prp/jupyter-stack/container_registry
 [b-data]: https://github.com/b-data