Update links for MONAI website and docs (#1876)

* Update documentation URLs to use GitHub Pages and ReadTheDocs

Replace references to monai.io domain with project-monai.github.io for
the website and monai.readthedocs.io for documentation.

* Update Slack channel invite link

---------

Co-authored-by: SACHIDANAND ALLE <sachidanand.alle@gmail.com>

Author: zephyrie

README.md

@@ -14,7 +14,7 @@ limitations under the License.
 # MONAI Label
 [![License](https://img.shields.io/badge/license-Apache%202.0-green.svg)](https://opensource.org/licenses/Apache-2.0)
 [![CI Build](https://github.com/Project-MONAI/MONAILabel/workflows/build/badge.svg?branch=main)](https://github.com/Project-MONAI/MONAILabel/commits/main)
-[![Documentation Status](https://readthedocs.org/projects/monailabel/badge/?version=latest)](https://docs.monai.io/projects/label/en/latest/?badge=latest)
+[![Documentation Status](https://readthedocs.org/projects/monailabel/badge/?version=latest)](https://monai.readthedocs.io/projects/label/en/latest/?badge=latest)
 [![PyPI version](https://badge.fury.io/py/monailabel.svg)](https://badge.fury.io/py/monailabel)
 [![Azure DevOps tests (compact)](https://img.shields.io/azure-devops/tests/projectmonai/monai-label/10?compact_message)](https://dev.azure.com/projectmonai/monai-label/_test/analytics?definitionId=10&contextType=build)
 [![Azure DevOps coverage](https://img.shields.io/azure-devops/coverage/projectmonai/monai-label/10)](https://dev.azure.com/projectmonai/monai-label/_build?definitionId=10)
@@ -27,7 +27,7 @@ open-source and easy-to-install ecosystem that can run locally on a machine with
 and client work on the same/different machine. It shares the same principles
 with [MONAI](https://github.com/Project-MONAI).
 
-Refer to full [MONAI Label documentations](https://docs.monai.io/projects/label/en/latest/index.html) for more details or check out our [MONAI Label Deep Dive videos series](https://www.youtube.com/playlist?list=PLtoSVSQ2XzyD4lc-lAacFBzOdv5Ou-9IA).
+Refer to full [MONAI Label documentations](https://monai.readthedocs.io/projects/label/en/latest/index.html) for more details or check out our [MONAI Label Deep Dive videos series](https://www.youtube.com/playlist?list=PLtoSVSQ2XzyD4lc-lAacFBzOdv5Ou-9IA).
 
 Refer to [MONAI Label Tutorial](https://github.com/Project-MONAI/tutorials/tree/main/monailabel) series for application and viewer workflows with different medical image tasks. Notebook-like tutorials are created for detailed instructions.
 
@@ -182,8 +182,8 @@ In addition, you can find a table of the basic supported fields, modalities, vie
 <pre>pip install -U monailabel</pre>
 
 MONAI Label supports the following OS with **GPU/CUDA** enabled. For more details instruction, please see the installation guides.
-- [Ubuntu](https://docs.monai.io/projects/label/en/latest/installation.html)
-- [Windows](https://docs.monai.io/projects/label/en/latest/installation.html#windows)
+- [Ubuntu](https://monai.readthedocs.io/projects/label/en/latest/installation.html)
+- [Windows](https://monai.readthedocs.io/projects/label/en/latest/installation.html#windows)
 
 ### GPU Acceleration (Optional Dependencies)
 Following are the optional dependencies which can help you to accelerate some GPU based transforms from MONAI. These dependencies are enabled by default if you are using `projectmonai/monailabel` docker.
@@ -401,15 +401,15 @@ the [contributing guidelines](https://github.com/Project-MONAI/MONAILabel/blob/m
 ## Community
 
 Join the conversation on Twitter [@ProjectMONAI](https://twitter.com/ProjectMONAI) or join
-our [Slack channel](https://projectmonai.slack.com/archives/C031QRE0M1C).
+our [Slack channel](https://join.slack.com/t/projectmonai/shared_invite/zt-3hucgm02q-i8Bn9XofDZs2UGOH4jUl4w).
 
 Ask and answer questions over
 on [MONAI Label's GitHub Discussions tab](https://github.com/Project-MONAI/MONAILabel/discussions).
 
 ## Additional Resources
 
-- Website: https://monai.io/
-- API documentation: https://docs.monai.io/projects/label
+- Website: https://project-monai.github.io/
+- API documentation: https://monai.readthedocs.io/projects/label
 - Code: https://github.com/Project-MONAI/MONAILabel
 - Project tracker: https://github.com/Project-MONAI/MONAILabel/projects
 - Issue tracker: https://github.com/Project-MONAI/MONAILabel/issues

sample-apps/endoscopy/README.md

@@ -106,7 +106,7 @@ interactive and automated segmentation.
   </summary>
 This model is currently trained to segment **Tool** from 2D in-body images.
 
-- Network: This model uses the [BasicUNet](https://docs.monai.io/en/latest/networks.html#basicunet) as the default network.
+- Network: This model uses the [BasicUNet](https://monai.readthedocs.io/en/stable/networks.html#basicunet) as the default network.
 - Labels: `{ "Tool": 1 }`
 - Dataset: The model is pre-trained over few in-body Images related to Endoscopy
 - Inputs: 3 channels.
@@ -119,7 +119,7 @@ This model is currently trained to segment **Tool** from 2D in-body images.
   <summary>
   <strong>ToolTracking</strong> is based on UNet for automated segmentation. This model works for single label segmentation tasks.
   </summary>
-- Network: This model uses the [FlexibleUNet](https://docs.monai.io/en/latest/networks.html#flexibleunet) as the default network.
+- Network: This model uses the [FlexibleUNet](https://monai.readthedocs.io/en/stable/networks.html#flexibleunet) as the default network.
 - Labels: `{ "Tool": 1 }`
 - Dataset: The model is pre-trained over few in-body Images related to Endoscopy
 - Inputs: 1 channel for the image modality
@@ -130,7 +130,7 @@ This model is currently trained to segment **Tool** from 2D in-body images.
   <summary>
   <strong>InBody/OutBody</strong> is based on SEResNet50 for classification. This model determines if tool is present or not (in-body vs out-body).
   </summary>
-- Network: This model uses the [SEResNet50](https://docs.monai.io/en/latest/networks.html#seresnet50) as the default network.
+- Network: This model uses the [SEResNet50](https://monai.readthedocs.io/en/stable/networks.html#seresnet50) as the default network.
 - Labels: `{ "InBody": 0, "OutBody": 1 }`
 - Dataset: The model is pre-trained over few in-body Images related to Endoscopy
 - Inputs: 1 channel for the image modality

sample-apps/monaibundle/README.md

@@ -14,7 +14,7 @@ limitations under the License.
 # MONAI Bundle Application
 The MONAIBundle App allows you to easily pull any MONAI Bundle from the [MONAI Model Zoo](https://github.com/Project-MONAI/model-zoo/tree/dev/models) and import it into MONAI Label. However, it's important to note that any MONAI Bundle used with MONAI Label must meet the following constraints:
 
-- It must comply with the [MONAI Bundle Specification](https://docs.monai.io/en/latest/mb_specification.html).
+- It must comply with the [MONAI Bundle Specification](https://monai.readthedocs.io/en/stable/mb_specification.html).
 - For inference, the bundle must define either an `inference.json` or `inference.yaml` file, and it must include the keys described in the bundle.py file located in the `monailabel/tasks/infer/` directory.
 - For training, the bundle must define either a `train.json` or `train.yaml file`, and it must include the keys described in the bundle.py file located in the `monailabel/tasks/train/` directory.
 - For multi-GPU training, the bundle must define either a `multi_gpu_train.json` or `multi_gpu_train.yaml` file.

sample-apps/radiology/README.md

@@ -67,7 +67,7 @@ monailabel start_server --app workspace/radiology --studies workspace/images --c
 
 ### Hybrid Radiology App with Models and Bundles
 
-Radiology app now supports loading models from local or from bundles in [MONAI Model Zoo](https://monai.io/model-zoo)
+Radiology app now supports loading models from local or from bundles in [MONAI Model Zoo](https://project-monai.github.io/model-zoo)
 
 ```bash
 # Example: Pick two models of spleen and multi-organ segmentation model, and two model-zoo bundles.
@@ -106,7 +106,7 @@ A command example to use active learning strategies with DeepEdit would be:
 
 > monailabel start_server --app workspace/radiology --studies workspace/images --conf models deepedit --conf skip_scoring false --conf skip_strategies false --conf epistemic_enabled true
 
-- Network: This model uses the DynUNet as the default network. It also comes with pretrained model for [UNETR](https://docs.monai.io/en/latest/networks.html#unetr). Researchers can define their own network or use one of the listed [here](https://docs.monai.io/en/latest/networks.html)
+- Network: This model uses the DynUNet as the default network. It also comes with pretrained model for [UNETR](https://monai.readthedocs.io/en/stable/networks.html#unetr). Researchers can define their own network or use one of the listed [here](https://monai.readthedocs.io/en/stable/networks.html)
 - Labels:
   ```json
   {
@@ -151,7 +151,7 @@ the model to learn on new organ.
 |----------------------|--------------------|-----------------------------------------------------------------|
 | preload              | true, **false**    | Preload model into GPU                                                                                |
 
-- Network: This App uses the [BasicUNet](https://docs.monai.io/en/latest/networks.html#basicunet) as the default network.
+- Network: This App uses the [BasicUNet](https://monai.readthedocs.io/en/stable/networks.html#basicunet) as the default network.
 - Labels:
   ```json
   [
@@ -191,7 +191,7 @@ the model to learn on new organ.
 | preload              | true, **false**    | Preload model into GPU                                          |
 | scribbles            | **true**, false    | Don't load the scribble models, useful for user studies         |
 
-- Network: This model uses the [UNet](https://docs.monai.io/en/latest/networks.html#unet) as the default network. Researchers can define their own network or use one of the listed [here](https://docs.monai.io/en/latest/networks.html)
+- Network: This model uses the [UNet](https://monai.readthedocs.io/en/stable/networks.html#unet) as the default network. Researchers can define their own network or use one of the listed [here](https://monai.readthedocs.io/en/stable/networks.html)
 - Labels
   ```json
   {
@@ -242,7 +242,7 @@ A command example to use active learning strategies with segmentation_spleen wou
 > monailabel start_server --app workspace/radiology --studies workspace/images --conf models segmentation_spleen --conf skip_scoring false --conf skip_strategies false --conf epistemic_enabled true
 
 
-- Network: This App uses the [UNet](https://docs.monai.io/en/latest/networks.html#unet) as the default network.
+- Network: This App uses the [UNet](https://monai.readthedocs.io/en/stable/networks.html#unet) as the default network.
 - Labels: `{ "Spleen": 1 }`
 - Dataset: The model is pre-trained over dataset: http://medicaldecathlon.com/
 - Inputs: 1 channel for the image modality
@@ -280,7 +280,7 @@ The difference between second and third stage is that third stage get a more fin
 |----------------------|--------------------|-----------------------------------------------------------------|
 | use_pretrained_model | **true**, false    | Disable this NOT to load any pretrained weights                 |
 
-- Network: This App uses the [UNet](https://docs.monai.io/en/latest/networks.html#unet) as the default network.
+- Network: This App uses the [UNet](https://monai.readthedocs.io/en/stable/networks.html#unet) as the default network.
 - Labels:
   ```json
   {