Wbc demo

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Tracking Colliding Cells

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Wbc demo

  1. 1. Tracking Colliding Cells <br />A collaboration between <br />UNC Charlotte and Carolinas Medical Center<br />
  2. 2. Video of white blood cells in vivo microscope<br />
  3. 3. As many cells move at a wide range of speeds…<br />Collisions<br />
  4. 4. abrupt<br />change<br />
  5. 5. Smoothness Constraint<br />Region A<br />broken tracks<br />Region A<br />Region A<br />robust tracks<br />Our Method<br />
  6. 6. Training<br />100 cell samples<br />100background samples<br />
  7. 7. Detecting <br />Classify each pixel as a Cell or Background<br />
  8. 8. Tracking<br />time<br />
  9. 9. Kalman Filter<br />Popular<br />Extensively used for tracking.<br />Optimal<br />Estimate the most probable state.<br />Simple<br />Two steps: predict and correct.<br />
  10. 10. No Collision<br />Collision<br />smooth<br />smooth & abrupt<br />reliability<br />flexibility<br />?<br />Kalman filter<br />
  11. 11. Multiple Hypotheses<br />H2<br />Non- <br />Colliding<br />Colliding<br />H1<br />H3<br />H4<br />
  12. 12. Example<br />Region B<br />Our method<br />
  13. 13. Comparisons<br />MH<br />SC<br />SH<br />
  14. 14. Conclusion<br />The first tracking method for colliding cells.<br />The reliability of the Kalman filter, the flexibility of multiple hypotheses.<br />Excellent cell positions coverage.<br />Non- <br />Colliding<br />Colliding<br />88%<br />
  15. 15. Thank you.<br />

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