An extensible, open-source PACS archive software that replaces traditional centralized databases with agile indexing and retrieval for medical images.
Dicoogle is an open-source PACS archive software designed for storing, indexing, and retrieving medical imaging data in DICOM format. It replaces traditional centralized database architectures with a more agile and extensible system that automatically extracts all metadata from images, including private DICOM tags, without requiring re-engineering.
Healthcare IT professionals, medical imaging researchers, and developers working on PACS systems, telemedicine platforms, or medical data analysis tools who need a flexible, open-source archive solution.
Developers choose Dicoogle for its extensible plugin architecture, platform independence, and ability to handle diverse DICOM metadata without configuration changes, making it ideal for both research and clinical environments where customization is key.
Dicoogle - Open Source PACS
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Supports custom plugins for indexing, querying, storage, and services, enabling tailored deployments for specific research or clinical needs, as detailed in the plugin development guide.
Uses Apache Lucene to index all DICOM metadata, including private tags, allowing free-text, keyword-based, and range-based queries without reconfiguration, demonstrated in the web services examples.
Runs on any system with Java, avoiding vendor lock-in and proprietary dependencies, making it suitable for diverse environments from research labs to cloud deployments.
Provides a user-friendly web application for management and search, plus RESTful web services for programmatic access, as shown in the setup and usage sections for indexing and exporting data.
Requires manual copying of jar files, plugin configuration via XML files, and understanding of URI schemes, which can be cumbersome and error-prone for new users, as outlined in the setup instructions.
Core functionalities like indexing and storage depend on separate plugins that must be downloaded and configured, adding overhead and potential points of failure compared to all-in-one solutions.
Customization requires developing plugins with Java and Maven, demanding significant technical expertise, and documentation is fragmented across the README, learning pack, and wiki.