🔬 Active Segmentation

Active Segmentation is an interactive image segmentation and classification plugin for ImageJ that leverages both machine learning and geometric features. It enables biologists and researchers to perform pixel-level classification and whole image segmentation without requiring deep machine learning expertise.

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📌 Table of Contents

• About
• Features
• Prerequisites
• Installation
• Usage
• Project Structure
• Contributing
• License

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📖 About

Active Segmentation integrates:

• Expert domain knowledge via partial ground truth labeling
• Geometric feature extraction based on multi-scale signal processing
• Machine learning classifiers (Random Forest, SVM via Weka)

It supports two main workflows:

1. Image Segmentation — pixel-level classification of microscopic images
2. Image Classification — whole image classification using the same pipeline

Originally developed at Zuse Institute Berlin (ZIB) and published in:

Vohra, S.K.; Prodanov, D. The Active Segmentation Platform for Microscopic Image Classification and Segmentation. Brain Sci. 2021, 11, 1645.

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✨ Features

• Interactive segmentation using machine learning
• Support for multiple classifiers via Weka (Random Forest, SVM, etc.)
• Geometric and differential invariant feature extraction
• Multi-scale signal processing pipeline
• SQLite-based feature model persistence
• Extensible filter and transform plugin architecture
• Works as an ImageJ plugin — no separate installation needed

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🛠 Prerequisites

Before setting up the project, make sure you have the following installed:

Tool	Version	Link
Java JDK	8 or later	https://www.oracle.com/java/technologies/downloads/
Eclipse IDE	Latest	https://www.eclipse.org/downloads/
ImageJ	Latest	https://imagej.net/ij/index.html
Weka	3.8+	https://www.cs.waikato.ac.nz/ml/weka/
Git	Latest	https://git-scm.com/

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🚀 Installation

Step 1: Fork the Repository

1. Go to sumit3203/ACTIVESEGMENTATION
2. Click the "Fork" button in the top right corner
3. This creates a copy under your account at https://github.com/YOUR_USERNAME/ACTIVESEGMENTATION

Step 2: Clone Your Fork

Open a terminal and run:

git clone https://github.com/YOUR_USERNAME/ACTIVESEGMENTATION
cd ACTIVESEGMENTATION
git remote add upstream https://github.com/sumit3203/ACTIVESEGMENTATION
git remote -v

Step 3: Import into Eclipse

1. Open Eclipse IDE
2. Go to File → Import → Existing Projects into Workspace
3. Select the cloned ACTIVESEGMENTATION folder
4. Eclipse will auto-detect the project using .project and .classpath

Step 4: Add Dependencies

1. Right-click the project → Build Path → Add External JARs
2. Add all .jar files from the jars/ folder in the project root

Step 5: Build the Plugin JAR

1. Right-click ActSeg.jardesc → Create JAR
2. This will generate the plugin JAR file

Step 6: Install in ImageJ

1. Copy the generated JAR into ImageJ's plugins/ directory
2. Launch ImageJ
3. Find Active Segmentation under the Plugins menu

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🖥 Usage

Image Segmentation Mode

1. Open a microscopic image in ImageJ
2. Launch Active Segmentation from Plugins menu
3. Draw ROIs (Regions of Interest) on the image to provide ground truth labels
4. Select desired features and a classifier
5. Click Train to train the model
6. Click Segment to apply segmentation

Image Classification Mode

1. Open a set of images in ImageJ
2. Launch Active Segmentation
3. Label sample images for each class
4. Train and classify the full dataset

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📁 Project Structure

ACTIVESEGMENTATION/
├── src/                          # Java source code
│   ├── Active_Segmentation_.java # Main ImageJ plugin entry point
│   ├── FAbout.java               # About dialog UI
│   ├── activeSegmentation/       # Core segmentation logic
│   ├── dsp/                      # Digital signal processing / filters
│   ├── ijaux/                    # ImageJ auxiliary utilities
│   └── test/                     # Test classes
├── jars/                         # External dependency JARs (Weka, ImageJ)
├── docs/                         # Project documentation
├── resources/                    # Icons and UI resources
├── plugins.config                # ImageJ plugin registration
├── ActSeg.jardesc                # JAR build descriptor
└── README.md                     # This file

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🤝 Contributing

Contributions are welcome! Here's how to get started:

1. Fork the repository
2. Create a new branch for your feature or fix:

git checkout -b feature/your-feature-name

3. Make your changes
4. Commit with a clear message:

git commit -m "feat: describe your change here"

5. Push to your fork:

git push origin feature/your-feature-name

6. Open a Pull Request against the master branch

Contribution Ideas

• Add unit tests using JUnit
• Improve Javadoc on core interfaces (IFilter, IMoment)
• Add support for new image filters
• Improve UI/UX of the plugin panels
• Add support for 3D volumetric images

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📄 License

This project is licensed under the terms found in the LICENSE file.

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📬 Contact

For questions or suggestions, please open an issue on GitHub.