A NOVEL MULTIPLE PARTICLE TRACKING ALGORITHM FOR NOISY IN VIVO DATA BY MINIMAL PATH OPTIMIZATION WITHIN THE SPATIO-TEMPORAL VOLUME
Automated tracking of fluorescent particles in living cells is vital for subcellular stoichoimetry analysis [1, 2]. Here, a new automatic tracking algorithm is described to track multiple particles, based on minimal path optimization. After linking feature points frame-by-frame, spatio-temporal data...
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| Format: | Conference item |
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2009
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| Summary: | Automated tracking of fluorescent particles in living cells is vital for subcellular stoichoimetry analysis [1, 2]. Here, a new automatic tracking algorithm is described to track multiple particles, based on minimal path optimization. After linking feature points frame-by-frame, spatio-temporal data from time-lapse microscopy are combined together to construct a transformed 3D volume. The trajectories are then generated from the minimal energy path as defined by the solution of the time-dependent partial differential equation using a gray weighted distance transform dynamic programming method. Results from simulated and experimental data demonstrate that our novel automatic method gives sub-pixel accuracy even for very noisy images. © 2009 IEEE. |
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