1 / 25

Inexpensive, Easy-To-Use, and Feature-Rich Worm Tracking

WORM TRACKER 2.0. Inexpensive, Easy-To-Use, and Feature-Rich Worm Tracking. Part I. A Short Overview. The Benefits. Inexpensive Easy-to-Use Feature Rich A simple pipeline to Analysis Well-Documented (easily extended, updated, and maintained). Inexpensive.

pembroke
Download Presentation

Inexpensive, Easy-To-Use, and Feature-Rich Worm Tracking

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. WORM TRACKER 2.0 Inexpensive, Easy-To-Use, and Feature-Rich Worm Tracking

  2. Part I A Short Overview

  3. The Benefits • Inexpensive • Easy-to-Use • Feature Rich • A simple pipeline to Analysis • Well-Documented (easily extended, updated, and maintained)

  4. Inexpensive • Works FAST and beautifully with CHEAP (<$30) USB cameras. • Supports most stages: • Ludl & Prior now • National Instruments/Parker later • Works well with any computer: • Windows, Mac, & Unix variants • Does NOT require any software purchases.

  5. Easy-To-Use • Plug-n-Play • Plug the camera and stage into the PC. • Download and run the software. • Automatic Calibration • Stage-to-Pixels • Pixels-to-Microns • Tracking • Simple functionality is on the main screen. • Advanced Options and tweaks are also easily accessible.

  6. Attaching Your USB Camera What Do You Need?

  7. Attaching Your USB Camera ( Don’t worry it’ll be on the web page  ) 1. Open it up. 2. Remove the lens. 3. Add glue. 4. Glue on the C-mount.

  8. Voila!

  9. Show Me The Video!

  10. Feature Rich LIMITS • NO Recording Limits • Unlimited Length (as long as you have space) • ANY Frame Rate & Resolution • Track EVEN in Difficult Conditions, e.g.: • Young Worms • Thick Food • Contamination • Plate Edges • Time-Lapse recording. • An easy pipeline to our Analysis software • Over 100 Features extracted.

  11. More Features (x,y) = • Continually Log the worm’s Real-World Location. • Snap images in many formats: • JPG, GIF, BMP, PNG • Advanced control over recording: • Resolution • Video Format • Frame Rate • Time/Frame/Intermittent Lengths • Advanced control over tracking: • Boundaries • Thresholds • Coordinate stage movements with recording to Minimize Blur

  12. Standardization • Identical Video & Tracking Data REGARDLESS of the Hardware & OS Configuration • Allows Searchable Databases of videos & analyses • Dry Lab Experimentation • Phenotypic Identification • Cross-Experimental Comparisons • Meta Studies • Open Source for reuse (e.g., A Neuronal Imaging Tracker)

  13. Extensive Documentation • Design overview • FAQ • Tutorials • Troubleshooting guide • Javadoc Web Pages • ANY Java programmer can Understand, Edit, & Extend the code • Easy Updates & Maintenance

  14. Example:Supporting a New Motorized Stage (A Tutorial Document will be Included with the Software) • Fill in a motorized stage wrapper. • ~5 Lines of Java • Translate “Move” into the stage’s language • A text command for the serial port. • ~1 Line of Java • Or, call the API to move the stage. • A Few Lines of code

  15. Part II The Details

  16. Tracking Overview

  17. Worm Tracker 2.0 Java Media Framework USB Camera USB Camera USB Camera The Java Media Framework • Supports most USB Cameras • Synchronizes multiple data sources • Cameras, microphones, etc. • Can Multiplex and Combine data sources Example: 3 synchronized videos • Cyan & yellow filtered fluorescent neurons. • A low magnification worm behavior video. • Monitor while recording for Real-Time Video Analysis

  18. The Tracking Algorithm • Convert the image to Grayscale. • Find the Worm: • Threshold to find the foreground (worm). • Find an appropriate “8-connected” component. • FindMotion: • Ignore tracked in/out image boundaries. • Subtract successive frames (motion). • Threshold to find movement (worm). • Find large 8-connected components. • Re-Center the worm upon boundary violation.

  19. Adaptive Thresholding • The Otsu Method • Assume a bimodal distribution of pixels (worm & background). • Find a threshold to split the modalities: • Maximize the variance between modalities. • Minimize the variance within modalities. • O(# of pixels) – Optimal!

  20. Adaptive Thresholding

  21. 8-Connected Components • 8 Neighbors (vs. 4 – no diagonals) • “Two Strategies to Speed Up Connected Component Labeling”, 2005, Wu et al. • 1 forward scan • Union find • Decision trees • Sequential memory access • Area and Boundary discovery during the scan. • O(# of Pixels) – Optimal!

  22. Movement Detection • Calibrate to Ignore Video Noise Automatically establish thresholds: • Minimum area • ∆ pixel value • Subtract successive Frames • Motion = large 8-connected components where: | ∆ pixel value | > 0 • Move stage to Keep Motion In Bounds

  23. Movement Detection

  24. Acknowledgements • Chris Cronin • Ryan Lustig • Kathleen, Katie, Callie, & Andrew • Bill Schafer & Paul Sternberg • Yechiam Yemini (My Dad) • Zhaoyang (John) Feng

  25. Contact Us • Email • Ev • eyemini@ucsd.edu • Chris • cjc@caltech.edu • WWW • http://sourceforge.net/projects/worm-tracking

More Related