QuPath is an open, flexible, extensible software platform for bioimage analysis. It is designed to support a wide range of tasks in digital pathology, including cell and nuclei detection, tissue classification, and biomarker quantification.
- Supported Applications
- Installing QuPath
- Install MONAI Label Extension From Binaries
- Building MONAI Label Extension from source
- Using the Plugin
Users can find supported applications in the sample-apps folder under the radiology section. They'll find models like DeepEdit, DeepGrow, Segmentation, and more. These applications can be used to create and refine labels for various medical imaging tasks.
To use MONAILabel with QuPath, you first need to download QuPath from https://qupath.github.io/. Once you have QuPath installed, you can install the MONAILabel plugin using one of the following methods
- Download qupath-extension-monailabel-0.3.0.jar.
- Drag the jar file onto the running QuPath application window (black screen area) to install the extension.
Note: If you have previously installed the MONAILabel plugin, make sure to remove/uninstall the extension before updating.
To build the latest extension jar using OpenJDK 11 or later with gradle, follow these steps:
- Navigate to the directory where you cloned the MONAILabel repository and then navigate to the
plugins/qupathfolder. - Run the following command to build the jar file:
gradle clean build- The output extension jar will be located under
build/libs. - Drag the jar file onto QuPath to install the extension.
- Make sure the MONAILabel Server URL is correctly set in the Preferences.
- Open a sample Whole Slide Image in QuPath (which is shared as studies for MONAILabel server).
- Add or select a rectangle ROI to run annotations using MONAI Label models.
- For interactive models (e.g. DeepEdit), you can choose to provide positive and negative points through the Annotation panel.