ROCm-LS · SwRaw · Apr 1, 2026 · Mar 24, 2026 · Mar 24, 2026 · Mar 24, 2026
diff --git a/.gitignore b/.gitignore
@@ -165,3 +165,4 @@ runs
 *.pth
 
 *zarr/*
+docs/sphinx/_toc.yml
diff --git a/LICENSE b/LICENSE
@@ -186,7 +186,7 @@
       same "printed page" as the copyright notice for easier
       identification within third-party archives.
 
-   Copyright [yyyy] [name of copyright owner]
+   Copyright [2025] [AMD CORPORATION]
 
    Licensed under the Apache License, Version 2.0 (the "License");
    you may not use this file except in compliance with the License.

diff --git a/docs/conf.py b/docs/conf.py
@@ -35,10 +35,10 @@
 all_article_info_author = ""
 
 # Dynamically extract component version
-version_number = "1.0.0"
+version_number = "1.5.0"
 
 # for PDF output on Read the Docs
-project = "MONAI 1.0.0 for AMD ROCm"
+project = "MONAI 1.5.0 on ROCm"
 author = "Advanced Micro Devices, Inc."
 copyright = "Copyright (c) 2025 Advanced Micro Devices, Inc. All rights reserved."
 version = version_number
@@ -68,4 +68,4 @@
 
 html_title = f"{project} documentation"
 
-external_projects_current_project = "MONAI for AMD ROCm"
+external_projects_current_project = "MONAI on ROCm"
diff --git a/docs/index.rst b/docs/index.rst
@@ -4,17 +4,17 @@
 
 .. _index:
 
-*********************************
-MONAI for AMD ROCm documentation
-*********************************
+*****************************
+MONAI on ROCm documentation
+*****************************
 
-The Medical Open Network for AI (MONAI) is a domain-optimized, open-source framework based on PyTorch, explicitly designed for deep learning in healthcare imaging. MONAI 1.0.0 for AMD ROCm is a HIP port of `MONAI upstream version 1.5.0 <https://monai.readthedocs.io/en/stable/whatsnew_1_5.html>`_. It is API-compatible with upstream MONAI without requiring any code changes.
+The `Medical Open Network for AI (MONAI) <https://project-monai.github.io/>`_ is a domain-optimized, open-source framework based on PyTorch, explicitly designed for deep learning in healthcare imaging. MONAI 1.5.0 on ROCm is a HIP port of `MONAI upstream version 1.5.0 <https://monai.readthedocs.io/en/stable/whatsnew_1_5.html>`_. It is API-compatible with upstream MONAI without requiring any code changes.
 
-MONAI for AMD ROCm, a ROCm-enabled version of `MONAI <https://project-monai.github.io/>`_, is built on top of `PyTorch for AMD ROCm <https://pytorch.org/blog/pytorch-for-amd-rocm-platform-now-available-as-python-package/>`_, helping healthcare and life science innovators to leverage GPU acceleration with AMD Instinct GPUs for high-performance inference and training of medical AI applications.
+MONAI on ROCm is built on top of `PyTorch for AMD ROCm <https://pytorch.org/blog/pytorch-for-amd-rocm-platform-now-available-as-python-package/>`_, helping healthcare and life science innovators to leverage GPU acceleration with AMD Instinct™ GPUs for high-performance inference and training of medical AI applications.
 
-MONAI for AMD ROCm offers open, scalable, and high-performance solutions for life science and healthcare workloads.
+MONAI on ROCm offers open, scalable, and high-performance solutions for life science and healthcare workloads.
 
-The MONAI for AMD ROCm key features include:
+The MONAI on ROCm key features include:
 
 - Flexible preprocessing for multidimensional medical imaging data
 
@@ -26,7 +26,7 @@ The MONAI for AMD ROCm key features include:
 
 .. note::
 
-  MONAI for AMD ROCm is in an early access state. Running production workloads is not recommended.
+  MONAI 1.5.0 on ROCm is in an early access state. Running production workloads is not recommended.
 
 The code is open and hosted at `<https://github.com/ROCm-LS/monai>`_.
 
@@ -37,7 +37,7 @@ The documentation is structured as follows:
 
   .. grid-item-card:: Install
 
-    * :ref:`Installation <installing-monai>`
+    * :ref:`installing-monai`
 
   .. grid-item-card:: Reference
 
@@ -46,10 +46,10 @@ The documentation is structured as follows:
 
   .. grid-item-card:: Related content
 
-    * `MONAI blog <https://rocm.blogs.amd.com/artificial-intelligence/monai-rocm/README.html>`_
+    * `MONAI on ROCm blog <https://rocm.blogs.amd.com/artificial-intelligence/monai-rocm/README.html>`_
 
-To contribute to MONAI for AMD ROCm, refer to
-`Contributing to MONAI for AMD ROCm <https://github.com/ROCm-LS/monai/blob/main/CONTRIBUTING.md>`_.
+To contribute to MONAI on ROCm, refer to
+`Contributing to MONAI on ROCm <https://github.com/ROCm-LS/monai/blob/main/CONTRIBUTING.md>`_.
 
 You can find licensing information on the
 :doc:`Licensing <license>` page.
diff --git a/docs/install/installation.rst b/docs/install/installation.rst
@@ -4,15 +4,15 @@
 
 .. _installing-monai:
 
-==============================
-Installing MONAI for AMD ROCm
-==============================
+============================
+MONAI on ROCm installation
+============================
 
-This topic discusses how to install MONAI for AMD ROCm using the following options:
+To install MONAI on ROCm, you have the following options:
 
-- :ref:`From source (for developers) <source-install>`
+- :ref:`Use package manager <package-install>` (recommended)
 
-- :ref:`Using package manager (for users) <package-install>`
+- :ref:`Build from source <source-install>`
 
 System requirements
 --------------------
@@ -23,30 +23,30 @@ System requirements
 
 - Python version: 3.10
 
-- AMD GPU: AMD Instinct MI300X GPUs
+- AMD Instinct™ GPU: MI300X
 
 - `PyTorch for AMD ROCm <https://pytorch.org/blog/pytorch-for-amd-rocm-platform-now-available-as-python-package/>`_ version: 2.8.0+rocm 6.4
 
-- NumPy 1.24 and later and earlier than 3.0
+- NumPy version: No earlier than 1.24 and no later than 2.4
 
-For more information about dependencies, see the ``requirements*.txt`` file.
+For the complete list of dependencies, see the `requirements.txt <https://github.com/ROCm-LS/monai/blob/main/requirements.txt>`_ file.
 
-.. _source-install:
+.. _package-install:
 
-Installing from source
------------------------
+Installing using package manager
+----------------------------------
 
-To build MONAI for AMD ROCm from source, follow the steps given in this section. This installation method should be used by MONAI for AMD ROCm developers. If you're a MONAI for AMD ROCm user, see :ref:`package-install`.
+To install MONAI on ROCm using package manager, follow the steps given in this section.
 
-1. Set up the Docker image using the ROCm Docker image from Dockerhub.
+1. Set up the Docker image using the ROCm Docker image from Docker Hub.
 
    .. code-block:: shell
 
       docker pull rocm/dev-ubuntu-22.04
       docker run --cap-add=SYS_PTRACE --ipc=host --privileged=true   \
          --shm-size=512GB --network=host --device=/dev/kfd     \
          --device=/dev/dri --group-add video -it               \
-         -v $HOME:$HOME  --name ${LOGNAME}_monai               \
+         -v $HOME:$HOME  --name ${LOGNAME}_rocm                \
                                            rocm/dev-ubuntu-22.04:6.4.1
 
 2. Install the required system dependencies.
@@ -59,62 +59,56 @@ To build MONAI for AMD ROCm from source, follow the steps given in this section.
       sudo add-apt-repository -y "deb https://apt.kitware.com/ubuntu/ $(lsb_release -cs) main"
       sudo apt update
       sudo apt install -y git wget gcc g++ ninja-build git-lfs       \
-                  yasm libopenslide-dev python3.10-venv        \
-                  cmake rocjpeg rocjpeg-dev rocthrust-dev      \
-                  hipcub hipblas hipblas-dev hipfft hipsparse  \
-                  hiprand rocsolver rocrand-dev rocm-hip-sdk
+                        yasm libopenslide-dev python3.10-venv        \
+                        cmake rocjpeg rocjpeg-dev rocthrust-dev      \
+                        hipcub hipblas hipblas-dev hipfft hipsparse  \
+                        hiprand rocsolver rocrand-dev rocm-hip-sdk
 
-3. Download the latest version of MONAI for AMD ROCm from the git repository:
+3. Create and activate the development environment.
 
    .. code-block:: shell
 
-      git clone git@github.com:ROCm-LS/monai.git
-      cd monai
+      python3 -m venv monai_dev
+      source monai_dev/bin/activate
+      pip install --upgrade pip
 
-4. Create and activate the development environment for building MONAI for AMD ROCm.
+4. Install the required Python dependencies.
 
    .. code-block:: shell
 
-      python3 -m venv monai_dev
-      source monai_dev/bin/activate
-      pip install --upgrade pip
-      pip install torch torchvision torchaudio      \
-                  --index-url https://download.pytorch.org/whl/rocm6.4
+      pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.4
       pip install amd-hipcim --extra-index-url=https://pypi.amd.com/simple
-      pip install -r requirements-dev.txt -c amd-constraints.txt
-
-5. Build and install MONAI for AMD ROCm on a ROCm based AMD system using the development environment.
 
-   To build and install the development version of MONAI for AMD ROCm, use:
+5. Install the optional dependencies depending on the workload.
 
    .. code-block:: shell
 
-      BUILD_MONAI=1 FORCE_CUDA=1 python3 setup.py develop
+      pip install ITK nibabel gdown tqdm lmdb psutil pandas einops mlflow \
+            pynrrd clearml transformers pydicom fire ignite         \
+            parameterized tensorboard pytorch-ignite onnx
 
-   To build and package an optimized wheel for installation, use:
+6. Install MONAI on ROCm from the AMD PyPI repository.
 
    .. code-block:: shell
 
-      BUILD_MONAI=1 FORCE_CUDA=1 python3 setup.py develop -O1 bdist_wheel
-
-   The preceding command builds the package in non-debug mode and the wheel file is generated under the ``dist`` directory.
+      pip install amd-monai --extra-index-url=https://pypi.amd.com/simple
 
-.. _package-install:
+.. _source-install:
 
-Installing using package manager
-----------------------------------
+Building from source
+-----------------------
 
-To install MONAI for AMD ROCm using package manager, follow the steps given in this section. This installation method should be used by MONAI for AMD ROCm users. If you're a MONAI for AMD ROCm developer, see :ref:`source-install`
+To build MONAI on ROCm from source, follow the steps given in this section.
 
-1. Set up the Docker image using the ROCm Docker image from Dockerhub.
+1. Set up the Docker image using the ROCm Docker image from Docker Hub.
 
    .. code-block:: shell
 
       docker pull rocm/dev-ubuntu-22.04
       docker run --cap-add=SYS_PTRACE --ipc=host --privileged=true   \
          --shm-size=512GB --network=host --device=/dev/kfd     \
          --device=/dev/dri --group-add video -it               \
-         -v $HOME:$HOME  --name ${LOGNAME}_rocm                \
+         -v $HOME:$HOME  --name ${LOGNAME}_monai               \
                                            rocm/dev-ubuntu-22.04:6.4.1
 
 2. Install the required system dependencies.
@@ -127,54 +121,60 @@ To install MONAI for AMD ROCm using package manager, follow the steps given in t
       sudo add-apt-repository -y "deb https://apt.kitware.com/ubuntu/ $(lsb_release -cs) main"
       sudo apt update
       sudo apt install -y git wget gcc g++ ninja-build git-lfs       \
-                        yasm libopenslide-dev python3.10-venv        \
-                        cmake rocjpeg rocjpeg-dev rocthrust-dev      \
-                        hipcub hipblas hipblas-dev hipfft hipsparse  \
-                        hiprand rocsolver rocrand-dev rocm-hip-sdk
+                  yasm libopenslide-dev python3.10-venv        \
+                  cmake rocjpeg rocjpeg-dev rocthrust-dev      \
+                  hipcub hipblas hipblas-dev hipfft hipsparse  \
+                  hiprand rocsolver rocrand-dev rocm-hip-sdk
 
-3. Create and activate the development environment.
+3. Download the latest version of MONAI on ROCm from the GitHub repository:
 
    .. code-block:: shell
 
-      python3 -m venv monai_dev
-      source monai_dev/bin/activate
-      pip install --upgrade pip
+      git clone git@github.com:ROCm-LS/monai.git
+      cd monai
 
-4. Install the required Python dependencies.
+4. Create and activate the development environment for building MONAI on ROCm.
 
    .. code-block:: shell
 
-      pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.4
+      python3 -m venv monai_dev
+      source monai_dev/bin/activate
+      pip install --upgrade pip
+      pip install torch torchvision torchaudio      \
+                  --index-url https://download.pytorch.org/whl/rocm6.4
       pip install amd-hipcim --extra-index-url=https://pypi.amd.com/simple
+      pip install -r requirements-dev.txt -c amd-constraints.txt
 
-5. Install the optional dependencies depending on the workload.
+5. Build and install MONAI on ROCm on a ROCm-based AMD system using the development environment.
+
+   To build and install the development version of MONAI on ROCm, use:
 
    .. code-block:: shell
 
-      pip install ITK nibabel gdown tqdm lmdb psutil pandas einops mlflow \
-            pynrrd clearml transformers pydicom fire ignite         \
-            parameterized tensorboard pytorch-ignite onnx
+      BUILD_MONAI=1 FORCE_CUDA=1 python3 setup.py develop
 
-6. Install MONAI optimized for AMD Instinct GPUs from the AMD PyPi repository.
+   To build and package an optimized wheel for installation, use:
 
    .. code-block:: shell
 
-      pip install amd-monai --extra-index-url=https://pypi.amd.com/simple
+      BUILD_MONAI=1 FORCE_CUDA=1 python3 setup.py develop -O1 bdist_wheel
+
+   The preceding command builds the package in non-debug mode and the wheel file is generated under the ``dist`` directory.
 
 Verify installation
 --------------------
 
-Use these commands to verify the MONAI for AMD ROCm installation:
+Use these commands to verify the MONAI on ROCm installation:
 
-- Print MONAI for AMD ROCm version.
+- Print the MONAI on ROCm version.
 
   .. code-block:: shell
 
    $ python -c "import monai; print(monai.__version__)"
 
-   1.0.0
+   1.5.0
 
-- Print MONAI for AMD ROCm package info.
+- Print the MONAI on ROCm package info.
 
   .. code-block:: shell
 

diff --git a/docs/reference/model-zoo.rst b/docs/reference/model-zoo.rst
@@ -8,24 +8,24 @@
 MONAI Model Zoo
 ****************
 
-The `MONAI Model Zoo <https://project-monai.github.io/model-zoo.html#/>`_ is a hub for researchers and data scientists to share, discover, and deploy the latest models from across the biomedical imaging community. By utilizing the standardized `MONAI Bundle format <https://monai.readthedocs.io/en/latest/bundle_intro.html>`_, you can easily `get started <https://github.com/Project-MONAI/tutorials/tree/main/model_zoo>`_ on building workflows or integrating new models into your projects.
+The `MONAI Model Zoo <https://project-monai.github.io/model-zoo.html#/>`_ is a hub for researchers and data scientists to share, discover, and deploy the latest models from across the biomedical imaging community. By using the standardized `MONAI Bundle format <https://monai.readthedocs.io/en/latest/bundle_intro.html>`_, you can easily start building workflows or integrating new models into your projects with the help of `tutorials <https://github.com/Project-MONAI/tutorials/tree/main/model_zoo>`_.
 
-MONAI for AMD ROCm provides seamless compatibility with the vast majority of models in the Model Zoo, helping both researchers and clinicians to accelerate state-of-the-art AI pipelines directly on AMD Instinct GPUs. Segmentation, detection, and classification models, including 2D and 3D workflows, run out of the box with minimal setup.
+MONAI on ROCm provides seamless compatibility with the vast majority of models in the Model Zoo, helping both researchers and clinicians to accelerate state-of-the-art AI pipelines directly on AMD Instinct™ GPUs. Segmentation, detection, and classification models, including 2D and 3D workflows, run out of the box with minimal setup.
 
 EXAONEPath model (hf_exaonepath-crc-msi-predictor) on ROCm
 -----------------------------------------------------------
 
-EXAONEPath 2.0 is a foundation model designed to deliver highly efficient, directly supervised patch-level representation learning for whole-slide images (WSIs). Except for a few other model zoo entries exclusively designed for NVIDIA, advanced models for computational pathology, such as EXAONEPath 2.0, are now supported on AMD hardware.
-Unlike typical patch-based self-supervised learning (SSL), EXAONE Path 2.0 leverages end-to-end slide-level supervision for powerful biomarker and molecular characteristic prediction with improved data efficiency.
+EXAONEPath 2.0 is a foundation model designed to deliver highly efficient, directly supervised patch-level representation learning for whole-slide images (WSIs). Except for a few other model zoo entries designed exclusively for specific hardware, advanced computational pathology models, such as EXAONEPath 2.0, are now supported on AMD hardware.
+Unlike typical patch-based self-supervised learning (SSL), EXAONEPath 2.0 leverages end-to-end slide-level supervision for powerful biomarker and molecular characteristic prediction with improved data efficiency.
 
 .. _set-exaonepath:
 
 Setting up EXAONEPath 2.0 on ROCm
 -----------------------------------
 
-To run EXAONEPath 2.0 on AMD platforms using MONAI for AMD ROCm, follow these steps:
+To run EXAONEPath 2.0 on AMD platforms using MONAI on ROCm, follow these steps:
 
-1. Install MONAI. For installation instructions, see :ref:`installing-monai`.
+1. Install MONAI on ROCm. For installation instructions, see :ref:`installing-monai`.
 
 2. Clone the EXAONEPath 2.0 repo:
 
@@ -69,6 +69,6 @@ Key takeaways
 
 - Most MONAI Model Zoo models run out of the box on ROCm, fully utilizing the AMD Instinct GPUs.
 
-- EXAONEPath 2.0, which was previously exclusive to NVIDIA, is now supported on AMD platforms using MONAI for AMD ROCm. The setup instructions are provided in :ref:`set-exaonepath`.
+- EXAONEPath 2.0 is now supported on AMD platforms using MONAI on ROCm. The setup instructions are provided in :ref:`set-exaonepath`.
 
-This reinforces MONAI for AMD ROCm as a truly open, high-performance AI platform, that removes vendor lock-in and unleashes broader access to foundational pathology models.
+This reinforces MONAI on ROCm as a truly open, high-performance AI platform, that removes vendor lock-in and unleashes broader access to foundational pathology models.
diff --git a/docs/reference/support-limitations.rst b/docs/reference/support-limitations.rst
@@ -8,13 +8,11 @@
 Supported features and limitations
 ===================================
 
-This topic discusses the features and limitations for MONAI 1.0.0 for AMD ROCm.
+This topic discusses the supported features and limitations of MONAI 1.5.0 on ROCm as compared to the `MONAI upstream version 1.5.0 <https://github.com/Project-MONAI/MONAI/releases/tag/1.5.0>`_.
 
 Features
 ---------
 
-Here are the MONAI for AMD ROCm features:
-
 - Deep learning inference
 
   - Accelerated inference for MONAI models using AMD ROCm and `HIP <https://rocm.docs.amd.com/projects/HIP/en/latest/>`_ backends.
@@ -31,7 +29,7 @@ Here are the MONAI for AMD ROCm features:
 
 - GPU acceleration
 
-  - Leverages AMD Instinct GPUs for high-throughput inference.
+  - Leverages AMD Instinct™ GPUs for high-throughput inference.
 
   - Delivers optimized memory and compute performance for large-scale medical datasets.
 
@@ -59,14 +57,14 @@ Here are the MONAI for AMD ROCm features:
 
   - Provides access to a wide collection of pretrained models from the `MONAI Model Zoo <https://project-monai.github.io/model-zoo.html#/>`_, ready for fine-tuning on custom datasets.
 
-  - Facilitates utilizing the `MONAI Bundle format <https://monai.readthedocs.io/en/latest/bundle_intro.html>`_ to easily `get started <https://github.com/Project-MONAI/tutorials/tree/main/model_zoo>`_ on building workflows or integrating new models into your projects.
+  - Facilitates using the `MONAI Bundle format <https://monai.readthedocs.io/en/latest/bundle_intro.html>`_ to easily start building workflows or integrating new models into your projects with the help of `tutorials <https://github.com/Project-MONAI/tutorials/tree/main/model_zoo>`_.
 
-  For more information on Model Zoo, see :ref:`model-zoo`.
+For more information about the MONAI Model Zoo, see :ref:`model-zoo`.
 
 Limitations
 ------------
 
-- MONAI for AMD ROCm only supports features from amd-cupy later than 13.5.1 and hipCIM 1.0.00 and later.
+- MONAI on ROCm only supports features from amd-cupy 13.5.1 and later, and hipCIM 25.10.00 and later.
 
 - There is no support for:
Original file line number	Diff line number	Diff line change
Expand Up		@@ -165,3 +165,4 @@ runs
		*.pth

		zarr/
		docs/sphinx/_toc.yml