ImageJ2: ImageJ for the next generation of scientific image data

Area of Science:

• Scientific imaging
• Biological sciences
• Physical sciences

Background:

• ImageJ is a widely used, open-source image analysis program in scientific research.
• Its extensibility and ease of use fostered a large, diverse user community.
• Technical limitations and a growing user base necessitated a software engineering overhaul.

Purpose of the Study:

• To engineer a next-generation ImageJ (ImageJ2) with enhanced flexibility and extensibility.
• To address the demands of modern scientific imaging paradigms and requirements.
• To improve interoperability and support for large, N-dimensional datasets.

Main Methods:

• Complete rewrite of the ImageJ codebase.
• Redesigned plugin mechanism for enhanced extensibility.
• Decoupled data model from the user interface.
• Emphasis on integration with external applications.

Main Results:

• ImageJ2 offers a robust new plugin framework for community-driven extensions.
• The redesigned data model supports arbitrarily large, N-dimensional datasets.
• Full decoupling of data model and user interface improves modularity.
• Maintained backward compatibility with classic ImageJ for seamless migration.

Conclusions:

• ImageJ2 provides a flexible framework to support current and future scientific imaging requirements.
• The improvements facilitate new method development and deployment to a diverse audience.
• Future work will focus on algorithm implementation and expanded collaborations.