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Slicer module for RadCoPilot (#63)
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diazandr3s authored Jan 24, 2025
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160 changes: 160 additions & 0 deletions plugins/RadCoPilot_Slicer/.gitignore
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35 changes: 35 additions & 0 deletions plugins/RadCoPilot_Slicer/CMakeLists.txt
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#-----------------------------------------------------------------------------
set(MODULE_NAME RadCoPilot)

#-----------------------------------------------------------------------------
set(MODULE_PYTHON_SCRIPTS
${MODULE_NAME}.py
${MODULE_NAME}Lib/__init__.py
${MODULE_NAME}Lib/client.py
)

set(MODULE_PYTHON_RESOURCES
Resources/Icons/${MODULE_NAME}.png
Resources/Icons/refresh-icon.png
Resources/Icons/upload.svg
Resources/UI/${MODULE_NAME}.ui
)

#-----------------------------------------------------------------------------
slicerMacroBuildScriptedModule(
NAME ${MODULE_NAME}
SCRIPTS ${MODULE_PYTHON_SCRIPTS}
RESOURCES ${MODULE_PYTHON_RESOURCES}
WITH_GENERIC_TESTS
)

#-----------------------------------------------------------------------------
if(BUILD_TESTING)

# Register the unittest subclass in the main script as a ctest.
# Note that the test will also be available at runtime.
slicer_add_python_unittest(SCRIPT ${MODULE_NAME}.py)

# Additional build-time testing
add_subdirectory(Testing)
endif()
45 changes: 45 additions & 0 deletions plugins/RadCoPilot_Slicer/README.md
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# RadCoPilot

A 3D Slicer module that integrates radiology copilots for enhanced medical image analysis and interpretation.

![](./Screenshots/3.png)

## Overview

RadCoPilot is a module for 3D Slicer that creates an interactive bridge between medical imaging and AI-powered radiology copilots. By leveraging the NVIDIA Holoscan platform, this tool enables seamless integration of advanced AI models for both 2D and 3D medical image analysis.

## Key Features

**Interactive Analysis**
- Real-time communication with radiology copilots via REST APIs
- Support for both 2D and 3D medical image analysis
- Direct volume transmission capabilities

**AI Integration**
- Seamless deployment of AI models through NVIDIA Holoscan
- Advanced medical imaging insights and interpretation
- Support for state-of-the-art models like MONAI VILA-M3

## Usage

1. Load your medical image volume in 3D Slicer
2. Launch the RadCoPilot module
3. Submit your query to the copilot
4. Review the AI-generated insights

## License

This project is licensed under the MIT License.

## Acknowledgments

This project builds upon several key technologies and resources:

- NVIDIA Holoscan SDK
- East River Imaging
- RadImageNet dataset
- MONAI VILA-M3

## Contact

For questions and support, please open an issue in the GitHub repository.
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