A novel multiple particle tracking algorithm for noisy in vivo data by minimal path optimization within the spatio-temporal volume

Authors:
Quan Xue;Mark C. Leake
Affiliations:
Clarendon Laboratory, Oxford Physics, University of Oxford, Parks Road, Oxford, UK and Oxford Centre for Integrative Systems Biology, South Parks Road, Oxford, UK;Clarendon Laboratory, Oxford Physics, University of Oxford, Parks Road, Oxford, UK and Oxford Centre for Integrative Systems Biology, South Parks Road, Oxford, UK
Venue:
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Year:
2009

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Abstract

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.