Welcome to iCLOTS’ documentation!

iCLOTS is an open source software for cellular microscopy image analysis, with a special focus on assays that incorporate microfluidic devices or flow chambers that apply fluidic forces. Completely standalone, it requires no coding experience and offers a simple and intuitive interactive GUI interface.

Check out our General information about iCLOTS section to learn more and get started.

Note

iCLOTS is open-source, and as such is completely free to download or to modify for your own use. For users who code, we welcome all improvements to code or functionality via pull requests on our github page. This project is under active development and our team is committed to creating a useful tool that meets the needs of the larger biosciences and biomedical research communities. Please feel free to reach out to help@iCLOTS.org with any questions, requests for help, or suggestions.

Contents

• General information about iCLOTS
  • General information
  • Output files
  • Interactive design
  • Experimental considerations
• Getting started
  • Downloading and opening iCLOTS in Mac OS
  • Downloading and opening iCLOTS in Windows OS
• Adhesion applications
  • Brightfield microscopy adhesion
  • Fluorescence microscopy adhesion
  • Filopodia and protrusion counter
  • Transient adhesion
• Single cell tracking applications
  • Brightfield microscopy single cell tracking
  • Fluorescence microscopy single cell tracking
  • Channel flow and deformability
• Multi-scale accumulation and occlusion
  • Region of interest image processing
  • Image processing for a microfluidic device with complex geometry
  • Image processing for a microfluidic microchannels
• Velocity application
  • Quantification of velocity timecourse and profile
• Video editing tools
  • Choose a region of interest (ROI)
  • Crop a video to a specified frame range
  • Edit the contrast of files
  • Convert an image sequence to a video
  • Normalize range of pixel intensity values
  • Resize file(s)
  • Rotate file(s)
  • Convert a video to an image sequence
• Machine learning-enabled interpretation
  • Post-processing clustering algorithm application
• Tips for reporting computational results
  • Reporting image analysis results
  • Reporting machine learning results
• Software information
  • Accessing source code
  • Open source packages utilized
  • Other excellent software projects
  • Data availability