A Hitchhiker's guide through the bio-image analysis software universe.

Area of Science:

• Life Sciences
• Computational Biology
• Bioimaging

Background:

• Computational methods are essential for extracting, quantifying, and visualizing microscopy imaging data in modern life sciences.
• The past decade has seen a significant increase in available software packages for biological image analysis.
• Keeping track of numerous image analysis platforms, tool collections, and emerging technologies is challenging.

Purpose of the Study:

• To provide a conservative overview of frequently used software for biological image analysis.
• To offer insights into emerging tools and technologies in the field.
• To guide researchers in selecting the most suitable image analysis platform for their specific needs.

Main Methods:

• Review of software utilized in daily routine for microscopy image analysis.
• Identification and discussion of emerging software and technologies.
• Development of a framework for platform selection based on user requirements.

Main Results:

• A curated overview of essential image analysis software.
• Insights into novel and developing tools for bioimaging.
• A decision-making guide for selecting appropriate software platforms.

Conclusions:

• Choosing the right image analysis software is critical for efficient life science research.
• Considerations for platform selection include image data type, team expertise, infrastructure, community support, time, and budget.
• This work aims to simplify the selection process and highlight valuable tools for the research community.