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Recognition, Tracking, and Data Acquisition for Microscopic Worms

Recognition, Tracking, and Data Acquisition for Microscopic Worms. ECPE 491: Senior Design Professor Mani Mina. Client : Dr. Santosh Pandey , Microfluidics Lab Graduate Supervisor: Roy Lycke Ryan Alley, Team Leader Colin Ray, Communicator Laith Abbas, Webmaster Shan Zhong

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Recognition, Tracking, and Data Acquisition for Microscopic Worms

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  1. Recognition, Tracking, and Data Acquisition for Microscopic Worms ECPE 491: Senior Design Professor Mani Mina

  2. Client: Dr. SantoshPandey, Microfluidics Lab • Graduate Supervisor: Roy Lycke • Ryan Alley, Team Leader • Colin Ray, Communicator • Laith Abbas, Webmaster • Shan Zhong • ShushengXu Group 03: Worm Tracking

  3. Background • C. elegans • What are C. elegans? • Why are C. elegansuseful? • How are C. elegansstudied? • Behavior • Qualitative vs. quantitative data • How to gather quantitative data? Problem Statement Group 03: Worm Tracking

  4. Group 03: Worm Tracking • Academic research • MBFBioscience—WormLab • Similarities between existing solutions • Distinguishing characteristics Market Survey

  5. Group 03: Worm Tracking • The software shall support the following video compression codecs: • Microsoft Video 1 • Intel Indeo • The software shall support input video frame-rates between 1 and 30 frames-per-second. • The software shall prompt the user to enter video parameters. • The interface shall support singular and batch selection and processing of video files. Functional Requirements

  6. Group 03: Worm Tracking • Upon completion of analysis, the software shall provide a confidence level in its worm assessments, based upon video quality (resolution, noise, etc..). • The software shall identify C. eleganswith a success rate of at least the aforementioned confidence level, as confirmed by human judgment of the video*. In addition, it shall not give a false-positive for any non-worm artifact. Functional Requirements *A bed of test-bench videos shall be chosen for this assessment by the client, Selected to test a variety of situations

  7. Group 03: Worm Tracking • Analysis shall provide, at a minimum, the X-Y coordinates of worm centroid, head, and tail over the duration of a given video, as well as the derived velocity and acceleration from the aforementioned worm data. • Additionally, the analysis shall also fit a spline to each worm’s curvature for each frame and present this spline graphically. Functional Requirements

  8. Group 03: Worm Tracking • The software shall be well-documented • The software shall run on the target computers without additional hardware • The software shall be easy-to-use by a lab technician • The software shall process video at no less than 10 MB of video data per second • The software and any support files shall be wrapped in a single installer Non-Functional Requirements

  9. Group 03: Worm Tracking • Input videos must be a minimum of 20 frames in length. • No more than five worms per unit volume (1 cm x 1 cm x 100 microns). • Potential Risks • In the case that our software fails, data will have to extracted from the video manually. Non-Functional Requirements

  10. Group 03: Worm Tracking • Typical Usecase: • Lab technician records videos, noting magnification and scale • Lab technician starts program, is prompted for file(s) and relevant information (magnification and scale) • Video is analyzed by software and outputs data as file, informs user System Design

  11. Group 03: Worm Tracking • Details Detailed Design

  12. Group 03: Worm Tracking • Currently reads and processes pre-recorded video • Performs background subtraction • Finds centroid and outputs coordinates to CSV • Graphically fits spline • Limitations: • Number of worms • No collision-detection TODO: add screenshots~! Prototype

  13. Group 03: Worm Tracking • Ryan Alley • Interface Description, Methodology • Colin Ray • Video Input Layer, Background Subtractor • Laith Abbas • Webpage, Documentation • Shan Zhong • Centroid Finder, Spline Fitting • ShushengXu • Centroid Finder, Spline Fitting Individual Contributions

  14. Group 03: Worm Tracking • Play a video!!!! • Metrics (human comparison, quality of videos, etc…) Test Plan

  15. Group 03: Worm Tracking • Hardware purchase not considered. • Open-Source platform provides free license. • Labor… free.  Cost Estimate

  16. Group 03: Worm Tracking • Prototype version 1.0 implemented • Lessons learned: • Need to further explore potential algorithms • Frame-by-frame processing • Model-based approach • Image analysis utilities Project Status

  17. Group 03: Worm Tracking • Gantt chart. Project Milestones

  18. Group 03: Worm Tracking References

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