Piximi - An Images to Discovery web tool for bioimages and beyond

Area of Science:

• Biological image analysis
• Deep learning applications
• Bioinformatics tools

Background:

• Deep learning accelerates biological image analysis but requires programming skills and tool installation.
• Existing tools pose barriers to entry for many researchers.
• Need for accessible, no-code deep learning solutions in life sciences.

Purpose of the Study:

• Introduce Piximi, a novel no-programming web application for deep learning-based biological image analysis.
• To lower the barrier to entry for utilizing advanced image analysis techniques in biological research.
• To provide researchers with rapid, secure, and intuitive image analysis capabilities.

Main Methods:

• Piximi is a web application accessible via any modern browser, requiring no installation.
• It features a client-only architecture for local data processing and enhanced security.
• Core modules include deep learning classification, image annotation, measurement, and segmentation.

Main Results:

• Piximi enables biological researchers to gain image insights within minutes.
• The tool supports common data and model formats for interoperability with existing workflows.
• Demonstrates successful integration of deep learning into an accessible, user-friendly interface.

Conclusions:

• Piximi democratizes deep learning-powered image analysis for a broader biological research community.
• Eliminates technical barriers, enabling faster and more efficient biological discovery.
• Facilitates wider adoption of advanced computational tools in life science research.