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    Wbc cmc talk Wbc cmc talk Presentation Transcript

    • Automated Tracking of Colliding Cells Nhat ‘Rich’ Nguyen Mentors : Min C. Shin, PhD & Toan T. Huynh, MD
    • Medicine Testing test object microscope cells video
    • Cells
      • White Blood Cells
      • Role in Immune System
      • Motion
        • Flowing
        • Rolling
        • Staying static
    • Tracking Cells Biologist interpret cell motions by tracking a few cells ?
    • Why few ? Tedious Expensive Subjective
    • Automated Tracking Cells Tedious Expensive Subjective Little effort* Inexpensive Objective
    • Colliding Cells Many cells moving at a wide range of speed  collision
      • Motion
      • Appearance
    • Automated Detection Radial Mean Kernel Background Frames A typical cell Difference
      • Based on appearance: Radial Mean
      • Based on movement: Background Subtraction
    • Automated Tracking Kalman smooth motion Collision abrupt motion
    • Multiple Hypothesis
    • Back-to-back Collision Eden’s Method Our Method Broken tracks Robust tracks
    • Roll-around Collision Eden’s Method Our Method Broken tracks Robust tracks
    • Conclusion
      • A method for reliably tracking multiple cells during collision.
      • Incorporated Kalman filter and multiple hypotheses for cases of no-collision, collision, during-collision and post-collision.
      • Improve when is compared to a previously proposed multiple cell tracking method.
    • Related Publications
      • S. J. Schmugge, S. Keller, N.R. Nguyen, R. Souvenir, T. H. Huynh, M. Clemens, M. C. Shin. "Segmentation of Vessels Cluttered with Cells using a Physics based Model". 11th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), New York, September 6-10 2008.
      • (submitting) N.R. Nguyen, S. Keller, T.H. Huynh, M.C. Shin. “Tracking Colliding Cells”. Microscopic Image Analysis with Applications in Biology (MIAAB), NIH Campus, Bethesda, MD September 03-04 2009.
    • QUESTIONS / SUGGESTIONS
    • Compare against Eden et al RMSE : root mean squared errors of position PTP : Positions tracked percentage TL : Track length As we compare our method to a previously published paper of Eden et al Collision Cases Only All Data Eden’s Method This Method Improvement Eden’s Method This Method Improvement RMSE (pixel) 14.6 8.9 40% 7.3 7.0 4% PTP (%) 61.5 93.0 51% 71.9 80.6 12% TL (frames) 7.3 12.6 71% 8.6 13.9 60%