NGFF-Converter

NGFF-Converter is an open source, easy-to-use GUI application developed by Glencoe Software, Inc. that converts bioimaging data into modern, open formats. It packages Glencoe Software's and the Open Microscopy Environment's world-renowned Bio-Formats proprietary conversion library into an intuitive desktop interface, making format conversion accessible to both everyday users and expert researchers.

Designed for academic and industrial R&D programs that rely on bioimaging, NGFF-Converter enables a cloud-based strategy for data management, analysis, and visualisation by supporting conversion to OME-NGFF and OME-TIFF — two open, unified formats suited to the demands of modern bioimaging workflows.

Supported Output Formats

• OME-NGFF: A new, cloud-friendly data format optimized for multi-dimensional bioimaging datasets, including those used in digital pathology, multiplexed imaging, and high content screening.
• OME-TIFF: The classic open format for bioimaging data, providing a well-established option for unifying data into a common, accessible structure.

Key Features and Capabilities

• Easy-to-use interface: The intuitive GUI was designed with users in mind, providing essential tools and functionality without unnecessary complexity.
• Cloud optimised: OME-NGFF output enables storage and analysis of bioimaging data in the cloud, making large-scale imaging workflows feasible for both academic and industrial settings.
• Full control: Customisable conversion options are available for expert users who require fine-grained control over the conversion process.
• Unified data: Support for both OME-NGFF and OME-TIFF allows teams to consolidate diverse proprietary formats into a single, open standard for streamlined data access and analysis.
• Bio-Formats integration: Leverages the widely trusted Bio-Formats library to support a broad range of proprietary bioimaging input formats.

Scalability and Workflow Integration

• Improves the scalability and flexibility of data management, analysis, and visualisation pipelines.
• Makes it feasible to adopt cloud-based strategies for R&D programs that depend on bioimaging data.
• Has been validated in real-world use cases, including a case study using OME-NGFF with the OMERO-CellProfiler Connector to enable scalable image analysis in the cloud.

NGFF-Converter is available as a free download and is open source, with source code hosted on GitHub and a public ChangeLog tracking releases. It is suitable for life sciences teams looking to modernise their bioimaging data infrastructure and take advantage of cloud-compatible, open data formats.